_id large_stringlengths 24 24 | hash large_stringlengths 16 16 | vocab_hash large_stringlengths 16 16 | vocab_size int64 1 2.4M | model_type large_stringclasses 4
values | num_merges float64 0 4.41M ⌀ | has_normalizer bool 2
classes | has_pre_tokenizer bool 2
classes | has_post_processor bool 2
classes | has_decoder bool 2
classes | num_added_tokens int64 0 479k | normalizer_type large_stringclasses 11
values | pre_tokenizer_type large_stringclasses 10
values | decoder_type large_stringclasses 9
values | normalizer_types listlengths 0 11.3k ⌀ | pre_tokenizer_types listlengths 1 35 ⌀ | decoder_types listlengths 0 24 ⌀ | tokenizer_id int64 0 24.8k | id large_stringlengths 7 122 | author stringlengths 2 41 ⌀ | base_models dict | downloads int64 0 206M | downloads_all_time int64 0 2.81B | gated stringclasses 3
values | created_at timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-11-03 14:41:54 | last_modified timestamp[us, tz=UTC]date 2020-12-11 21:34:15 2026-03-29 10:14:05 ⌀ | library_name stringclasses 36
values | likes int64 0 13.1k | trending_score float64 0 47 | model_index stringlengths 30 911k ⌀ | pipeline_tag stringclasses 46
values | safetensors stringlengths 30 122 ⌀ | siblings listlengths 0 10k ⌀ | sha stringlengths 40 40 ⌀ | tags listlengths 2 1.82k ⌀ | gguf stringclasses 789
values | config stringlengths 2 53.7k ⌀ | transformers_info dict | card_data stringlengths 234 905k ⌀ | card stringlengths 0 638k ⌀ | spaces null | licenses listlengths 1 3 ⌀ | datasets listlengths 1 289 ⌀ | languages listlengths 1 1.81k ⌀ | safetensors_params float64 0 1,019B ⌀ | gguf_params float64 0 122B ⌀ | metrics listlengths 1 15 ⌀ | architectures listlengths 1 6 ⌀ | tasks listlengths 1 6 ⌀ | modalities listlengths 1 4 ⌀ | input_modalities listlengths 1 3 ⌀ | output_modalities listlengths 1 4 ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
65203de7578e7da0d71891e5 | d6e6379268d2e729 | 0000e6c6a03fba1a | 32,003 | BPE | 61,249 | true | false | true | true | 6 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 513 | TinyLlama/TinyLlama-1.1B-Chat-v0.3 | TinyLlama | null | 2,207 | 443,572 | False | 2023-10-06T17:03:35Z | 2023-11-05T06:07:52Z | transformers | 43 | 0 | null | text-generation | {"parameters": {"F32": 1100060672}, "total": 1100060672} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 1ea93498c83d6d5aece90cf3b160aadf9f8875f8 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:cerebras/SlimPajama-627B",
"dataset:bigcode/starcoderdata",
"dataset:OpenAssistant/oasst_top1_2023-08-25",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["cerebras/SlimPajama-627B", "bigcode/starcoderdata", "OpenAssistant/oasst_top1_2023-08-25"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "... | <div align="center">
# TinyLlama-1.1B
</div>
https://github.com/jzhang38/TinyLlama
The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion tokens**. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs 🚀🚀. The training has started on 2023-0... | null | [
"apache-2.0"
] | [
"cerebras/SlimPajama-627B",
"bigcode/starcoderdata",
"OpenAssistant/oasst_top1_2023-08-25"
] | [
"en"
] | 1,100,060,672 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
679ca4adb6250d6fa38a8de4 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | unsloth/Qwen2.5-VL-7B-Instruct-unsloth-bnb-4bit | unsloth | {
"models": [
{
"_id": "6795ffcd88cd7c0294702a72",
"id": "Qwen/Qwen2.5-VL-7B-Instruct"
}
],
"relation": "quantized"
} | 18,172 | 528,830 | False | 2025-01-31T10:23:41Z | 2025-09-16T15:19:20Z | transformers | 51 | 0 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"chat_template.json",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"preprocessor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"video_preprocessor... | 02c0940169a4914b8a2388cba9e26132817c0ea7 | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"multimodal",
"unsloth",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0"... | null | {"architectures": ["Qwen2_5_VLForConditionalGeneration"], "model_type": "qwen2_5_vl", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "processor_config": {"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for me... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["Qwen/Qwen2.5-VL-7B-Instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ["multimodal", "unsloth"]} | # Qwen2.5-VL-7B-Instruct
<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Introduction
In the past five months since Qwen2-VL’s r... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"qwen2_5_vl",
"AutoModelForImageTextToText",
"Qwen2_5_VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
6594f05f754092f6b15cfe7c | f87ccc7d7c85fe32 | d743a27e139a5baf | 41,510 | BPE | 79,142 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 514 | universitytehran/PersianMind-v1.0 | universitytehran | null | 442 | 435,390 | False | 2024-01-03T05:27:59Z | 2024-09-05T17:30:41Z | transformers | 70 | 0 | null | text-generation | {"parameters": {"F32": 2048, "BF16": 6816321536}, "total": 6816323584} | [
".gitattributes",
"LICENSE",
"LLaMa2_LICENSE",
"PersianMind.jpg",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"pytorch_model-00001-of-00002.bin",
"pytorch_mo... | af603eeb074138e2a613fbc95d89f018afbd3041 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"multilingual",
"fa",
"en",
"arxiv:2401.06466",
"license:cc-by-nc-sa-4.0",
"co2_eq_emissions",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["multilingual", "fa", "en"], "library_name": "transformers", "license": "cc-by-nc-sa-4.0", "license_name": null, "license_link": null, "metrics": ["bleu", "comet", "accuracy", "perplexity", "spearmanr"], "model_name": null, "pipeline_tag": "text-... | <p align="center">
<img src="PersianMind.jpg" alt="PersianMind logo" width=200/>
</p>
# <span style="font-variant:small-caps;">PersianMind</span>
<span style="font-variant:small-caps;">PersianMind</span> is a cross-lingual Persian-English large language model.
The model achieves state-of-the-art results on Persia... | null | [
"cc-by-nc-sa-4.0"
] | null | [
"multilingual",
"fa",
"en"
] | 6,816,323,584 | null | [
"bleu",
"comet",
"accuracy",
"perplexity",
"spearmanr"
] | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f181a5b | f7b02c0b9d6f991b | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 29 | ydshieh/vit-gpt2-coco-en | ydshieh | null | 3,721 | 469,765 | False | 2022-03-02T23:29:05Z | 2025-12-02T16:56:22Z | transformers | 39 | 0 | null | image-to-text | {"parameters": {"F32": 239195904}, "total": 239195904} | [
".gitattributes",
"README.md",
"config.json",
"events.out.tfevents.1633443513.t1v-n-bb5dfd23-w-0.8655.0.v2",
"flax_model.msgpack",
"generation_config.json",
"generation_eval.json",
"merges.txt",
"model.safetensors",
"pipeline.py",
"preprocessor_config.json",
"pytorch_model.bin",
"report.txt"... | e46020106a48310f1eff33b3b31a9f139d752cc1 | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"safetensors",
"vision-encoder-decoder",
"image-text-to-text",
"image-to-text",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["VisionEncoderDecoderModel"], "model_type": "vision-encoder-decoder", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["image-to-text"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images... | ## Example
The model is by no means a state-of-the-art model, but nevertheless
produces reasonable image captioning results. It was mainly fine-tuned
as a proof-of-concept for the 🤗 FlaxVisionEncoderDecoder Framework.
The model can be used as follows:
**In PyTorch**
```python
import torch
import requests
from PIL... | null | null | null | null | 239,195,904 | null | null | [
"AutoModelForImageTextToText",
"vision-encoder-decoder",
"VisionEncoderDecoderModel"
] | [
"image-text-to-text",
"image-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
63623e7d19cf373a5fbea020 | ea197a153967759f | 1fcd51277d003941 | 50,000 | BPE | 48,016 | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | BPEDecoder | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"BPEDecoder"
] | 515 | Voicelab/herbert-base-cased-sentiment | Voicelab | null | 28,519 | 478,621 | False | 2022-11-02T09:55:09Z | 2023-03-20T11:40:07Z | transformers | 7 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 124445187}, "total": 124445701} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | ca028e48c7bae75f348e1d2a04d7a7beafb800cd | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"pl",
"license:cc-by-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["pl"], "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": null, "widget": [{"text": "Pani Katarzyno z jakiej racji moja pac... | <img src="https://public.3.basecamp.com/p/rs5XqmAuF1iEuW6U7nMHcZeY/upload/download/VL-NLP-short.png" alt="logo voicelab nlp" style="width:300px;"/>
# Sentiment Classification in Polish
```python
import numpy as np
from transformers import AutoTokenizer, AutoModelForSequenceClassification
id2label = {0: "negative", 1... | null | [
"cc-by-4.0"
] | null | [
"pl"
] | 124,445,701 | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6818bf3927e09c38fb64ea2e | bafc5e0c20be7cd8 | 82d3db801e5d7f68 | 49,152 | BPE | 48,900 | false | true | false | true | 17 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 115 | GoofyLM/N1 | GoofyLM | null | 13 | 430,125 | False | 2025-05-05T13:38:01Z | 2025-07-08T16:35:23Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F32": 134515008}, "total": 134515008} | [
".gitattributes",
"README.md",
"banner.png",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 550cc0ebe9c02b1eecad4a092503d4e6ca282769 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["text-generation-inference"], "new_version": "GoofyLM/N2-Nemo"} | null | null | [
"mit"
] | null | [
"en"
] | 134,515,008 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6650ff0e33fc744153d5194c | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | RedHatAI/Meta-Llama-3-70B-Instruct-FP8 | RedHatAI | null | 4,660 | 450,303 | False | 2024-05-24T20:56:46Z | 2024-07-18T19:09:22Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"BF16": 2102665216, "F8_E4M3": 68451041280}, "total": 70553706496} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00015.safetensors",
"model-00002-of-00015.safetensors",
"model-00003-of-00015.safetensors",
"model-00004-of-00015.safetensors",
"model-00005-of-00015.safetensors",
"model-00006-of-00015.safetensors",
"model-0... | 048a5ccf3b132339d2e0d2426010e2d8c61f4041 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"fp8",
"vllm",
"conversational",
"en",
"license:llama3",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "fp8"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_he... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "llama3", "license_name": null, "license_link": "https://llama.meta.com/llama3/license/", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["fp8", "vllm"]} | null | null | [
"llama3",
"https://llama.meta.com/llama3/license/"
] | null | [
"en"
] | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17f01d | e387f2f9dec84ea9 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 516 | prithivida/informal_to_formal_styletransfer | prithivida | null | 301 | 429,845 | False | 2022-03-02T23:29:05Z | 2021-06-19T08:30:19Z | transformers | 8 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | 472cedcfc522615f77e64bedc54b4ef710fe71d3 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | null | ## This model belongs to the Styleformer project
[Please refer to github page](https://github.com/PrithivirajDamodaran/Styleformer) | null | null | null | null | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
67a4476990df902092652358 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | unsloth/Qwen2.5-14B-Instruct-unsloth-bnb-4bit | unsloth | {
"models": [
{
"_id": "66e81cdaa3681387ffc12b55",
"id": "Qwen/Qwen2.5-14B-Instruct"
}
],
"relation": "quantized"
} | 30,444 | 682,579 | False | 2025-02-06T05:23:53Z | 2025-04-28T04:16:18Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"BF16": 2470237184, "F32": 837760, "U8": 12684275602}, "total": 15155350546} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
... | f38e4535425655bdf439dd8f47be11a9157081b1 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"qwen",
"conversational",
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:quantized:Qwe... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-14B-Instruct", "datasets": null, "eval_results": null, "language": ["zho", "eng", "fra", "spa", "por", "deu", "ita", "rus", "jpn", "kor", "vie", "tha", "ara"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name":... | <div>
<p style="margin-bottom: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/qwen-25-66fe4c08fb9ada518e8a0d3f">our collection</a> for versions of Qwen2.5 including 4-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em>Unsloth's <a href="https://unsloth.ai/blog/dynamic-... | null | [
"apache-2.0"
] | null | [
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara"
] | 15,155,350,546 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66c4fc3ea22fa65e17eb3d99 | f5e7f943c396c76b | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 52 | mlx-community/Phi-3.5-mini-instruct-4bit | mlx-community | null | 3,404 | 442,333 | False | 2024-08-20T20:27:42Z | 2024-08-24T06:12:14Z | transformers | 9 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_phi3.py",
"model.safetensors",
"model.safetensors.index.json",
"modeling_phi3.py",
"sample_finetune.py",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 7b2052fd882fe017300d4d42a4eb06a27b816af4 | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"nlp",
"code",
"mlx",
"conversational",
"custom_code",
"multilingual",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Phi3ForCausalLM"], "auto_map": {"AutoConfig": "configuration_phi3.Phi3Config", "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"}, "model_type": "phi3", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{% if message['role'] == 'system' and message['conten... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": "https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-gen... | # mlx-community/Phi-3.5-mini-instruct-4bit
The Model [mlx-community/Phi-3.5-mini-instruct-4bit](https://huggingface.co/mlx-community/Phi-3.5-mini-instruct-4bit) was converted to MLX format from [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) using mlx-lm version **0.17.0**.
#... | null | [
"mit",
"https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE"
] | null | [
"multilingual"
] | null | null | null | [
"AutoModelForCausalLM",
"phi3",
"Phi3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
687a098f61552cc5e8ac1e4b | b3310d158ab6e0dc | 66be3297e0980489 | 28,895 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 409 | OpenMed/OpenMed-NER-OrganismDetect-BioMed-335M | OpenMed | null | 93,373 | 817,699 | False | 2025-07-18T08:45:03Z | 2025-08-05T09:44:25Z | transformers | 1 | 0 | null | token-classification | {"parameters": {"BF16": 334095363}, "total": 334095363} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"openmed_vs_sota_grouped_bars.png",
"special_tokens_map.json",
"test_results.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | b1c947157ccfec95b574612c52bee2e24453b8b4 | [
"transformers",
"safetensors",
"bert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"species-recognition",
"taxonomy",
"organism-identification",
"biodiversity",
"species",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | null | null | [
"apache-2.0"
] | null | [
"en"
] | 334,095,363 | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66f0f7856e736af2c18af2f4 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | unsloth/Qwen2.5-14B-Instruct | unsloth | {
"models": [
{
"_id": "66e81cdaa3681387ffc12b55",
"id": "Qwen/Qwen2.5-14B-Instruct"
}
],
"relation": "finetune"
} | 13,402 | 548,897 | False | 2024-09-23T05:07:17Z | 2025-04-28T04:16:15Z | transformers | 11 | 0 | null | text-generation | {"parameters": {"BF16": 14770033664}, "total": 14770033664} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00006.safetensors",
"model-00002-of-00006.safetensors",
"model-00003-of-00006.safetensors",
"model-00004-of-00006.safetensors",
"model-00005-of-00006.safetensors",
"model-... | facfb1bad6443964128be460ff6c98928a4ad4ab | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"conversational",
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:f... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Aliba... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-14B-Instruct", "datasets": null, "eval_results": null, "language": ["zho", "eng", "fra", "spa", "por", "deu", "ita", "rus", "jpn", "kor", "vie", "tha", "ara"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name":... | # Finetune Llama 3.1, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a Qwen 2.5 (all model sizes) [free Google Colab Tesla T4 notebook](https://colab.research.google.com/drive/1Kose-ucXO1IBaZq5BvbwWieuubP7hxvQ?usp=sharing).
Also a [Qwen 2.5 conversational style notebook](https://colab.resear... | null | [
"apache-2.0"
] | null | [
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara"
] | 14,770,033,664 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
655dcf4ce20d902aa3f8b15e | f6bd53b02735a215 | 3f3879d485dc5e16 | 63,992 | BPE | 110,029 | true | false | false | true | 231 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 512 | 01-ai/Yi-34B-Chat | 01-ai | null | 32,287 | 533,378 | False | 2023-11-22T09:52:12Z | 2024-11-11T03:36:35Z | transformers | 357 | 0 | null | text-generation | null | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00015.safetensors",
"model-00002-of-00015.safetensors",
"model-00003-of-00015.safetensors",
"model-00004-of-00015.safetensors",
"model-00005-of-00015.safetensors",
"model-00006-of-00015.safetensors... | cf02cb50f2a03dead2fe205766a1c5598a90bf80 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2403.04652",
"arxiv:2311.16502",
"arxiv:2401.11944",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|startoftext|>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content']... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "widget": [{"example_title": "Yi-34B-Chat", "text": "hi", "outpu... | - they might want nothing more than destruction itself rather then anything else from their quest after immortality (and maybe someone should tell them about modern medicine)? In any event though – one thing remains true regardless : whether or not success comes easy depends entirely upon how much effort we put into co... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67b79c6c01ad68cfed14677a | b86074a73431b347 | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 434 | google/gemma-3-4b-pt | google | null | 167,934 | 1,348,681 | manual | 2025-02-20T21:19:40Z | 2025-03-21T16:13:41Z | transformers | 150 | 0 | null | image-text-to-text | {"parameters": {"BF16": 4300079472}, "total": 4300079472} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"preprocessor_config.json",
"processor_config.json",
"special_tokens_map.json",
"tokenizer.json",... | cc012e0a6d0787b4adcc0fa2c4da74402494554d | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"arxiv:1905.07830",
"arxiv:1905.10044",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1705.03551",
"arxiv:1911.01547",
"arxiv:1907.10641",
"arxiv:1903.00161",
"arxiv:2009.03300",
"arxiv:2304.06364",
"arxiv:2103.03874",
"ar... | null | {"architectures": ["Gemma3ForConditionalGeneration"], "model_type": "gemma3", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null, "extra_gated_heading": "Access Gemma on Hugging Face", "... | null | null | [
"gemma"
] | null | null | 4,300,079,472 | null | null | [
"AutoModelForImageTextToText",
"Gemma3ForConditionalGeneration",
"gemma3"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
632c074016faa31b24d73c6a | 8bc6b61a7b6c29c2 | 4c6e091e8dffb5aa | 30,003 | BPE | 29,740 | false | true | true | true | 7 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 299 | EleutherAI/polyglot-ko-5.8b | EleutherAI | null | 1,886 | 438,347 | False | 2022-09-22T06:57:04Z | 2023-06-07T05:03:38Z | transformers | 67 | 0 | null | text-generation | {"parameters": {"F16": 5885059072, "F32": 896, "BOOL": 117440512}, "total": 6002500480} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00013.safetensors",
"model-00002-of-00013.safetensors",
"model-00003-of-00013.safetensors",
"model-00004-of-00013.safetensors",
"model-00005-of-00013.safetensors",
"model-00006-of-00013.safetensors",
"model-0... | 581a4c3eebfac23536b3c9676bcfb05c6a97baa2 | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"ko",
"arxiv:2104.09864",
"arxiv:2204.04541",
"arxiv:2306.02254",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ko"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["pytorch", "causal-lm"]} | # Polyglot-Ko-5.8B
## Model Description
Polyglot-Ko is a series of large-scale Korean autoregressive language models made by the EleutherAI polyglot team.
| Hyperparameter | Value |
|... | null | [
"apache-2.0"
] | null | [
"ko"
] | 6,002,500,480 | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
665dc81577eb75d3b933f79f | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/Qwen2-72B-Instruct-AWQ | Qwen | {
"models": [
{
"_id": "66555421d17e141dcb225f7f",
"id": "Qwen/Qwen2-72B-Instruct"
}
],
"relation": "quantized"
} | 432 | 426,049 | False | 2024-06-03T13:41:41Z | 2024-08-21T10:19:47Z | transformers | 41 | 0 | null | text-generation | {"parameters": {"F16": 2493554688, "I32": 70464307200}, "total": 72957861888} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00011.safetensors",
"model-00002-of-00011.safetensors",
"model-00003-of-00011.safetensors",
"model-00004-of-00011.safetensors",
"model-00005-of-00011.safetensors",
"model-00006-of-0... | 26975fbe12cda45e38c0b99da62f1a7deab1bf25 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2309.00071",
"base_model:Qwen/Qwen2-72B-Instruct",
"base_model:quantized:Qwen/Qwen2-72B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"awq",
"de... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-72B-Instruct", "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "other", "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen2-72B-Instruct-AWQ/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "... | # Qwen2-72B-Instruct-AWQ
## Introduction
Qwen2 is the new series of Qwen large language models. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the instruction-tuned 72B Qwe... | null | [
"other",
"tongyi-qianwen",
"https://huggingface.co/Qwen/Qwen2-72B-Instruct-AWQ/blob/main/LICENSE"
] | null | [
"en"
] | 72,957,861,888 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64b7c10b6ab5d14ca70128c3 | 26d3953dcaee904b | 1fcd51277d003941 | 50,000 | BPE | 48,016 | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | BPEDecoder | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"BPEDecoder"
] | 517 | bardsai/twitter-emotion-pl-base | bardsai | null | 8 | 466,246 | False | 2023-07-19T10:55:07Z | 2023-09-18T08:23:29Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json",
"vocab.txt"
] | 128ef8ca9f5756983ca3f835bc5d7472dd748d3b | [
"transformers",
"pytorch",
"bert",
"text-classification",
"twitter",
"pl",
"dataset:datasets/tweet_eval",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["datasets/tweet_eval"], "eval_results": null, "language": "pl", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["f1", "accuracy", "precision", "recall"], "model_name": null, "pipeline_tag": null, "tags": ["text-classification", "twitter"],... | # Twitter emotion PL (base)
Twitter emotion PL (base) is a model based on [herbert-base](https://huggingface.co/allegro/herbert-base-cased) for analyzing emotion of Polish twitter posts. It was trained on the translated version of [TweetEval](https://www.researchgate.net/publication/347233661_TweetEval_Unified_Benchma... | null | null | [
"datasets/tweet_eval"
] | [
"pl"
] | null | null | [
"f1",
"accuracy",
"precision",
"recall"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
636e64b867692798149a6c29 | 07bf363e27d0a819 | 21be6968922e2f2a | 60,000 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 518 | eevvgg/bert-polish-sentiment-politics | eevvgg | null | 20 | 432,772 | False | 2022-11-11T15:05:28Z | 2024-05-23T14:14:59Z | transformers | 5 | 0 | [{"name": "PaReS-sentimenTw-political-PL", "results": [{"task": {"type": "sentiment-classification", "name": "Text Classification"}, "dataset": {"type": "tweets", "name": "tweets_2020_electionsPL"}, "metrics": [{"type": "f1", "value": 94.4, "verified": false}]}]}] | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | 819cccdf5a666f1fdde300f64afea64456aab7ae | [
"transformers",
"pytorch",
"bert",
"text-classification",
"text",
"sentiment",
"politics",
"pl",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"language": ["pl"], "metrics": ["accuracy", "f1"], "pipeline_tag": "text-classification", "tags": ["text", "sentiment", "politics"], "widget": [{"text": "Przykro patrze\u0107, a s\u0142ucha\u0107 si\u0119 nie da.", "example_title": "example 1"}, {"text": "Oczywi\u015bcie ze Pan Prezydent to nasza duma narodowa!!", "ex... | # PaReS-sentimenTw-political-PL
This model is a fine-tuned version of [dkleczek/bert-base-polish-cased-v1](https://huggingface.co/dkleczek/bert-base-polish-cased-v1) to predict 3-categorical sentiment.
Fine-tuned on 1k sample of manually annotated Twitter data.
Model developed as a part of ComPathos project: https://... | null | null | null | [
"pl"
] | null | null | [
"accuracy",
"f1"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
661e91a7ec5b53e102164c96 | 1a9c61552285a54f | 3085d01101e6b8e8 | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 397 | DiTy/bi-encoder-russian-msmarco | DiTy | {
"models": [
{
"_id": "621ffdc036468d709f175167",
"id": "DeepPavlov/rubert-base-cased"
}
],
"relation": "finetune"
} | 331 | 424,175 | False | 2024-04-16T14:56:39Z | 2024-08-02T06:38:34Z | sentence-transformers | 7 | 0 | [{"name": "rubert-bi-encoder-mmarcoRU", "results": [{"task": {"type": "Retrieval"}, "dataset": {"type": "unicamp-dl/mmarco", "name": "mMARCO (Russian)", "split": "test"}, "metrics": [{"type": "cos_sim-Recall@5", "value": 0.9997142857142856, "verified": false}, {"type": "cos_sim-MRR@10", "value": 0.9859809523809522, "ve... | sentence-similarity | {"parameters": {"F32": 177853440}, "total": 177853440} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 34530ed7a2fb02c5f04ca1a190502af3b798da4d | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"rubert",
"bi-encoder",
"retriever",
"msmarco",
"ru",
"dataset:unicamp-dl/mmarco",
"base_model:DeepPavlov/rubert-base-cased",
"base_model:finetune:DeepPavlov/rubert-base-cased",
"... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": "DeepPavlov/rubert-base-cased", "datasets": ["unicamp-dl/mmarco"], "language": ["ru"], "library_name": "sentence-transformers", "license": "mit", "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers", "rubert", "bi-encoder", "... | # DiTy/bi-encoder-russian-msmarco
This is a [sentence-transformers](https://www.SBERT.net) model based on a pre-trained [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) and finetuned with [MS-MARCO Russian passage ranking dataset](https://huggingface.co/datasets/unicamp-dl/mmarco):
I... | null | [
"mit"
] | [
"unicamp-dl/mmarco"
] | [
"ru"
] | 177,853,440 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
63c9686e4c74c79fff691e19 | 337fa60bc59000b3 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 496 | lucadiliello/bleurt-tiny-512 | lucadiliello | null | 11 | 421,891 | False | 2023-01-19T15:57:34Z | 2023-01-19T15:59:28Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | e29963cf5b5861836ad16fa3ae827183f0b47e17 | [
"transformers",
"pytorch",
"bleurt",
"text-classification",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BleurtForSequenceClassification"], "model_type": "bleurt", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": null
} | null | This model is based on a custom Transformer model that can be installed with:
```bash
pip install git+https://github.com/lucadiliello/bleurt-pytorch.git
```
Now load the model and make predictions with:
```python
import torch
from bleurt_pytorch import BleurtConfig, BleurtForSequenceClassification, BleurtTokenizer
... | null | null | null | null | null | null | null | [
"BleurtForSequenceClassification",
"AutoModelForSequenceClassification",
"bleurt"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
648210379d9941bade74c54b | 191e06b04083279c | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 26 | Iceland/quote-model-delta | Iceland | null | 2 | 420,249 | False | 2023-06-08T17:30:31Z | 2023-06-08T17:40:04Z | transformers | 1 | 0 | [{"name": "quote-model-delta", "results": []}] | token-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Jun08_17-30-24_658504ed21bb/events.out.tfevents.1686245436.658504ed21bb.929.0",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | eac2798e73b4777e7cf1a0af1c2ee3baac15eefc | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": "quote-model-delta", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# quote-model-delta
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased)... | null | [
"apache-2.0"
] | null | null | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66e97b8a06c986aea9f80811 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-14B-Instruct-GPTQ-Int4 | Qwen | {
"models": [
{
"_id": "66e81cdaa3681387ffc12b55",
"id": "Qwen/Qwen2.5-14B-Instruct"
}
],
"relation": "quantized"
} | 196,230 | 906,376 | False | 2024-09-17T12:52:26Z | 2024-10-09T12:27:46Z | transformers | 26 | 0 | null | text-generation | {"parameters": {"I32": 13212057600, "F16": 1557976064}, "total": 14770033664} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"... | 08fdbde5eea15cd2aae884125fbfd604dec19818 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compati... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-14B-Instruct", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-GPTQ-Int4/blob/main/LICENSE", "metrics": null, "model_name": null, "pip... | # Qwen2.5-14B-Instruct-GPTQ-Int4
## Introduction
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
- Significantly ... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-GPTQ-Int4/blob/main/LICENSE"
] | null | [
"en"
] | 14,770,033,664 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66a0ad271a26a235039cf729 | c6de6331832e687a | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 142 | shenzhi-wang/Llama3.1-8B-Chinese-Chat | shenzhi-wang | {
"models": [
{
"_id": "6698d8a0653e4babe21e1e7d",
"id": "meta-llama/Llama-3.1-8B-Instruct"
}
],
"relation": "quantized"
} | 5,440 | 443,878 | False | 2024-07-24T07:28:39Z | 2024-07-29T08:10:54Z | transformers | 264 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"gguf/llama3.1_8b_chinese_chat_f16.gguf",
"gguf/llama3.1_8b_chinese_chat_q4_k_m.gguf",
"gguf/llama3.1_8b_chinese_chat_q8_0.gguf",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-o... | 404a735a6205e5ef992f589b6d5d28922822928e | [
"transformers",
"safetensors",
"gguf",
"llama",
"text-generation",
"llama-factory",
"orpo",
"conversational",
"en",
"zh",
"arxiv:2403.07691",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:quantized:meta-llama/Llama-3.1-8B-Instruct",
"doi:10.57967/hf/2779",
"license:llama3.1"... | {"total": 8030261248, "architecture": "llama", "context_length": 131072, "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set co... | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Meta-Llama-3.1-8B-Instruct", "datasets": null, "eval_results": null, "language": ["en", "zh"], "library_name": "transformers", "license": "llama3.1", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["llama-factory", "... | > [!CAUTION]
> For optimal performance, we refrain from fine-tuning the model's identity. Thus, inquiries such as "Who are you" or "Who developed you" may yield random responses that are not necessarily accurate.
> [!IMPORTANT]
> If you enjoy our model, please **give it a star on our Hugging Face repo** and kindly [*... | null | [
"llama3.1"
] | null | [
"en",
"zh"
] | null | 8,030,261,248 | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17f0ec | c373ed05ad808e9b | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 519 | pszemraj/led-large-book-summary | pszemraj | null | 3,542 | 427,410 | False | 2022-03-02T23:29:05Z | 2025-12-29T03:38:09Z | transformers | 120 | 0 | [{"name": "pszemraj/led-large-book-summary", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "kmfoda/booksum", "type": "kmfoda/booksum", "config": "kmfoda--booksum", "split": "test"}, "metrics": [{"type": "rouge", "value": 31.7308, "name": "ROUGE-1", "verified": true, "verif... | summarization | {"parameters": {"F32": 459851865}, "total": 459851865} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"ds_config_zero2.json",
"evals-outputs/GAUNTLET.md",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json",
"vocab.json"
] | 600de3bbcdb1da15fc4a5a2eb3ca7436eee25409 | [
"transformers",
"pytorch",
"safetensors",
"led",
"text2text-generation",
"summarization",
"summary",
"longformer",
"booksum",
"long-document",
"long-form",
"en",
"dataset:kmfoda/booksum",
"arxiv:2105.08209",
"doi:10.57967/hf/0101",
"license:apache-2.0",
"license:bsd-3-clause",
"mod... | null | {"architectures": ["LEDForConditionalGeneration"], "model_type": "led", "tokenizer_config": {"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "norm... | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["kmfoda/booksum"], "language": ["en"], "license": ["apache-2.0", "bsd-3-clause"], "metrics": ["rouge"], "tags": ["summarization", "led", "summary", "longformer", "booksum", "long-document", "long-form"], "widget": [{"text": "large earthquakes along a given fault segment do not occur at random intervals be... | # led-large-book-summary
<a href="https://colab.research.google.com/gist/pszemraj/3eba944ddc9fc9a4a1bfb21e83b57620/summarization-token-batching.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
This model is a fine-tuned version of [allenai/led-large-16384](https... | null | [
"apache-2.0",
"bsd-3-clause"
] | [
"kmfoda/booksum"
] | [
"en"
] | 459,851,865 | null | [
"rouge"
] | [
"AutoModelForSeq2SeqLM",
"led",
"LEDForConditionalGeneration"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64ce0216d2a781d3f0d61830 | 382b5a4eb98f0296 | d965e4a9140ecf72 | 21,128 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 33 | BAAI/bge-base-zh | BAAI | null | 96,970 | 688,733 | False | 2023-08-05T08:02:30Z | 2023-10-12T03:37:45Z | transformers | 57 | 0 | null | feature-extraction | {"parameters": {"I64": 512, "F32": 102267648}, "total": 102268160} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 0e5f83d4895db7955e4cb9ed37ab73f7ded339b6 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"zh",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | **Recommend switching to newest [BAAI/bge-base-zh-v1.5](https://huggingface.co/BAAI/bge-base-zh-v1.5), which has more reasonable similarity distribution and same method of usage.**
<h1 align="center">FlagEmbedding</h1>
<h4 align="center">
<p>
<a href=#model-list>Model List</a> |
<a href=#frequen... | null | [
"mit"
] | null | [
"zh"
] | 102,268,160 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
64788a83ad83f3939b4c0ec1 | f0b30459222b62d4 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 36 | alirezamsh/quip-512-mocha | alirezamsh | null | 19 | 416,845 | False | 2023-06-01T12:09:39Z | 2024-03-21T11:22:19Z | transformers | 4 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 355360769}, "total": 355361283} | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"merges.txt",
"model.safetensors",
"predict_results_None.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"test_quip.py",
"tokenizer.json",
"tokenizer_config.json",
"train_results.json",
"trainer_... | f8a3ddef4072828cd4ea090b1121aaeaf2a9545c | [
"transformers",
"pytorch",
"safetensors",
"roberta",
"text-classification",
"en",
"dataset:mocha",
"license:bsd-3-clause",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["mocha"], "eval_results": null, "language": ["en"], "library_name": null, "license": "bsd-3-clause", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Answer Overlap Module of QAFactEval Metric
This is the span scorer module, used in [RQUGE paper](https://aclanthology.org/2023.findings-acl.428/) to evaluate the generated questions of the question generation task.
The model was originally used in [QAFactEval](https://aclanthology.org/2022.naacl-main.187/) for comp... | null | [
"bsd-3-clause"
] | [
"mocha"
] | [
"en"
] | 355,361,283 | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
669ab57f004e418e71901334 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | visegradmedia-emotion/Emotion_RoBERTa_polish6 | visegradmedia-emotion | null | 22 | 425,883 | False | 2024-07-19T18:50:39Z | 2024-08-13T23:41:39Z | transformers | 0 | 0 | [{"name": "Fine-tuned RoBERTa for Emotion Classification in Polish", "results": [{"task": {"type": "text-classification", "name": "Emotion Classification in Polish"}, "dataset": {"name": "Polish Custom Dataset", "type": "text"}, "metrics": [{"name": "Precision (Macro Avg)", "type": "precision", "value": 0.86, "verified... | text-classification | {"parameters": {"F32": 278048262}, "total": 278048262} | [
".gitattributes",
"README.md",
"checkpoint-11636/config.json",
"checkpoint-11636/model.safetensors",
"checkpoint-11636/optimizer.pt",
"checkpoint-11636/rng_state.pth",
"checkpoint-11636/scheduler.pt",
"checkpoint-11636/trainer_state.json",
"checkpoint-11636/training_args.bin",
"config.json",
"ev... | 95e56789b7d6123e56dd6165734e17cfb330337d | [
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"emotion-classification",
"roberta",
"fine-tuned",
"polish",
"pl",
"dataset:custom",
"license:mit",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["XLMRobertaForSequenceClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["custom"], "language": ["pl"], "license": "mit", "tags": ["emotion-classification", "roberta", "fine-tuned", "polish"], "model-index": [{"name": "Fine-tuned RoBERTa for Emotion Classification in Polish", "results": [{"task": {"type": "text-classification", "name": "Emotion Classification in Polish"}, "dat... | # Fine-tuned RoBERTa Model for Emotion Classification in Polish
## Model Description
This model is a fine-tuned version of the [RoBERTa](https://huggingface.co/roberta-base) model, specifically tailored for emotion classification tasks in Polish.
The model was trained to classify textual data into six emotional categ... | null | [
"mit"
] | [
"custom"
] | [
"pl"
] | 278,048,262 | null | null | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174696 | da443ce982f05a4c | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 51 | AlexKay/xlm-roberta-large-qa-multilingual-finedtuned-ru | AlexKay | null | 423 | 418,900 | False | 2022-03-02T23:29:04Z | 2022-07-19T15:33:20Z | transformers | 50 | 0 | null | question-answering | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 6cc14366f0cc95428a695d30594a93dd6935d800 | [
"transformers",
"pytorch",
"xlm-roberta",
"question-answering",
"en",
"ru",
"multilingual",
"arxiv:1912.09723",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaForQuestionAnswering"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false,... | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "ru", "multilingual"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # XLM-RoBERTa large model whole word masking finetuned on SQuAD
Pretrained model using a masked language modeling (MLM) objective.
Fine tuned on English and Russian QA datasets
## Used QA Datasets
SQuAD + SberQuAD
[SberQuAD original paper](https://arxiv.org/pdf/1912.09723.pdf) is here! Recommend to read!
## Evaluat... | null | [
"apache-2.0"
] | null | [
"en",
"ru",
"multilingual"
] | null | null | null | [
"AutoModelForQuestionAnswering",
"XLMRobertaForQuestionAnswering",
"xlm-roberta"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64bd7ff612d00c4589fb3027 | 67bab9d2e649936b | aa8af6ff55c14796 | 51,865 | BPE | 49,999 | false | true | true | true | 1,608 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 520 | NbAiLab/nb-whisper-large-beta | NbAiLab | null | 31 | 415,996 | False | 2023-07-23T19:31:02Z | 2023-07-24T18:05:01Z | transformers | 8 | 0 | null | automatic-speech-recognition | {"parameters": {"F32": 1543304960}, "total": 1543304960} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"export_models.sh",
"flax_model.msgpack",
"generation_config.json",
"ggml-model.bin",
"merges.txt",
"model.safetensors",
"normalizer.json",
"preprocessor_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_m... | a71a17e05948d59181a8867837ea3f7ec8f49688 | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"asr",
"hf-asr-leaderboard",
"no",
"nb",
"nn",
"en",
"dataset:NbAiLab/ncc_speech",
"dataset:NbAiLab/NST",
"dataset:NbAiLab/NPSC",
"arxiv:2212.04356",
"arxiv:1910.09700",
"... | null | {"architectures": ["WhisperForConditionalGeneration"], "model_type": "whisper", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": ... | {
"auto_model": "AutoModelForSpeechSeq2Seq",
"custom_class": null,
"pipeline_tag": "automatic-speech-recognition",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": ["NbAiLab/ncc_speech", "NbAiLab/NST", "NbAiLab/NPSC"], "eval_results": null, "language": ["no", "nb", "nn", "en"], "library_name": "transformers", "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": ["wer", "cer"], "model_name": null, "pipeline_tag": "automati... | # NB-Whisper Large (beta)
This is a **_public beta_** of the Norwegian NB-Whisper Large model released by the National Library of Norway. NB-Whisper is a series of models for automatic speech recognition (ASR) and speech translation, building upon the foundation laid by [OpenAI's Whisper](https://arxiv.org/abs/2212.04... | null | [
"cc-by-4.0"
] | [
"NbAiLab/ncc_speech",
"NbAiLab/NST",
"NbAiLab/NPSC"
] | [
"no",
"nb",
"nn",
"en"
] | 1,543,304,960 | null | [
"wer",
"cer"
] | [
"WhisperForConditionalGeneration",
"whisper",
"AutoModelForSpeechSeq2Seq"
] | [
"automatic-speech-recognition"
] | [
"multimodal"
] | [
"audio"
] | [
"text"
] |
629ecff510cd8bd636c8e215 | c667b81ba860e8b6 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 271 | Theivaprakasham/layoutlmv3-finetuned-invoice | Theivaprakasham | null | 645 | 418,450 | False | 2022-06-07T04:11:33Z | 2022-06-07T07:35:54Z | transformers | 24 | 0 | [{"name": "layoutlmv3-finetuned-invoice", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "Invoice", "type": "invoice", "args": "invoice"}, "metrics": [{"name": "Precision", "type": "precision", "value": 1, "verified": false}, {"name": "Recall", "type": "recall... | token-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"merges.txt",
"preprocessor_config.json",
"pytorch_model.bin",
"runs/Jun07_04-11-18_850ddd2feefa/1654575104.0822/events.out.tfevents.1654575104.850ddd2feefa.781.1",
"runs/Jun07_04-11-18_850ddd2feefa/events.out.tfevents.1654575104.850ddd2fee... | 817177117100efab28f4ecf162b1b1241df756cb | [
"transformers",
"pytorch",
"tensorboard",
"layoutlmv3",
"token-classification",
"generated_from_trainer",
"dataset:invoice",
"model-index",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LayoutLMv3ForTokenClassification"], "model_type": "layoutlmv3", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "cls_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normaliz... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoProcessor"
} | {"datasets": ["invoice"], "metrics": ["precision", "recall", "f1", "accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "layoutlmv3-finetuned-invoice", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "Invoice", "type": "invoice", "args": "i... | # LayoutLM-v3 model fine-tuned on invoice dataset
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the invoice dataset.
We use Microsoft’s LayoutLMv3 trained on Invoice Dataset to predict the Biller Name, Biller Address, Biller post_code, Due_date,... | null | null | [
"invoice"
] | null | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"LayoutLMv3ForTokenClassification",
"layoutlmv3"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
689252773b8900ddb9116aed | b86074a73431b347 | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 434 | google/gemma-3-270m | google | null | 87,092 | 830,635 | manual | 2025-08-05T18:50:31Z | 2025-08-14T07:35:01Z | transformers | 1,001 | 5 | null | text-generation | {"parameters": {"BF16": 268098176}, "total": 268098176} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 9b0cfec892e2bc2afd938c98eabe4e4a7b1e0ca1 | [
"transformers",
"safetensors",
"gemma3_text",
"text-generation",
"gemma3",
"gemma",
"google",
"arxiv:2503.19786",
"arxiv:1905.07830",
"arxiv:1905.10044",
"arxiv:1911.11641",
"arxiv:1705.03551",
"arxiv:1911.01547",
"arxiv:1907.10641",
"arxiv:2311.07911",
"arxiv:2311.12022",
"arxiv:241... | null | {"architectures": ["Gemma3ForCausalLM"], "model_type": "gemma3_text", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["gemma3", "gemma", "google"], "extra_gated_heading": "Access Gem... | null | null | [
"gemma"
] | null | null | 268,098,176 | null | null | [
"gemma3_text",
"AutoModelForCausalLM",
"Gemma3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
679e94cd49b5b38e4fa2d8d0 | dae53fc866d79bd6 | 1b9fd2d5dbbc6e0d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 83 | RedHatAI/DeepSeek-R1-Distill-Llama-70B-FP8-dynamic | RedHatAI | {
"models": [
{
"_id": "678e13bdda686d5964869153",
"id": "deepseek-ai/DeepSeek-R1-Distill-Llama-70B"
}
],
"relation": "quantized"
} | 13,974 | 457,824 | False | 2025-02-01T21:40:29Z | 2025-02-27T07:46:09Z | transformers | 10 | 0 | null | text-generation | {"parameters": {"BF16": 2109382656, "F8_E4M3": 68451041280}, "total": 70560423936} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00015.safetensors",
"model-00002-of-00015.safetensors",
"model-00003-of-00015.safetensors",
"model-00004-of-00015.safetensors",
"model-00005-of-00015.safetensors",
"model-00006-of-00015.safetensors",
"model-0... | fb3637a1165cec3832958bd72ebbe04021601489 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"deepseek",
"fp8",
"vllm",
"conversational",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"license:mit",
"text-generation-inference",
"endpoints_compatible"... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "compressed-tensors"}, "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "deepseek-ai/DeepSeek-R1-Distill-Llama-70B", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["deepseek", "fp8", "vllm"]} | null | null | [
"mit"
] | null | null | 70,560,423,936 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65e7939f196619c8f3dedfb7 | fc29ccd738d51f6b | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 1 | Delphia/twitter-spam-classifier | Delphia | null | 36 | 414,115 | False | 2024-03-05T21:50:23Z | 2024-04-02T19:56:43Z | transformers | 5 | 0 | null | text-classification | {"parameters": {"F32": 109483778}, "total": 109483778} | [
".gitattributes",
"README.md",
"checkpoint-60/config.json",
"checkpoint-60/model.safetensors",
"checkpoint-60/optimizer.pt",
"checkpoint-60/rng_state.pth",
"checkpoint-60/scheduler.pt",
"checkpoint-60/trainer_state.json",
"checkpoint-60/training_args.bin",
"config.json",
"model.safetensors",
"... | adee2f7efa31d3f37985156e68ef24921a61378e | [
"transformers",
"safetensors",
"bert",
"text-classification",
"autotrain",
"dataset:autotrain-57208-4mv8z/autotrain-data",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["autotrain-57208-4mv8z/autotrain-data"], "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["autotrain", "text-classification"], "widget": [{"text... | # Model Trained Using AutoTrain
- Problem type: Text Classification
Model trained on "Tesla" related tweets from X/Twitter to filter out spam tweets based on trolling, profanity, extreme political views, etc.
0 - Valid
1 - Spam
## Validation Metrics
loss: 0.4916948974132538
f1: 0.8059701492537313
precision: 0.7... | null | null | [
"autotrain-57208-4mv8z/autotrain-data"
] | null | 109,483,778 | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6532932ce760105846ea0652 | be2618dbd5e26199 | 7ce118731980e5c6 | 29,794 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 521 | ggrazzioli/cls_sentimento_sebrae | ggrazzioli | null | 9 | 413,134 | False | 2023-10-20T14:48:12Z | 2023-10-20T15:17:25Z | transformers | 5 | 0 | null | text-classification | {"parameters": {"I64": 512, "F32": 108925443}, "total": 108925955} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6f13a50d79e4a72afd2353e433926d17beb0178c | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"pt",
"dataset:ggrazzioli/cls_sentimento_sebrae",
"co2_eq_emissions",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["ggrazzioli/cls_sentimento_sebrae"], "eval_results": null, "language": ["pt"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text-classification"], "widget": [{"text": "Gostei muit... | # Model Trained
- Problem type: Classificação de sentimentos em dataset interno do Sebrae RS
- Model ID: 96390146647
- CO2 Emissions (in grams): 0.6308
- "id2label": {"0": "Negativo", "1": "Neutro", "2": "Positivo"}
## Validation Metrics
- Loss: 0.143
- Accuracy: 0.965
- Macro F1: 0.935
- Micro F1: 0.965
- Weighte... | null | null | [
"ggrazzioli/cls_sentimento_sebrae"
] | [
"pt"
] | 108,925,955 | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f181684 | 62ad3ad2b18d7994 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 81 | whaleloops/phrase-bert | whaleloops | null | 2,577 | 421,029 | False | 2022-03-02T23:29:05Z | 2021-11-03T15:04:02Z | sentence-transformers | 22 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6f68f4dc2d28aadefa038c79023dc7dfd51f6495 | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:2109.06304",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "tr... | # whaleloops/phrase-bert
This is the official repository for the EMNLP 2021 long paper [Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration](https://arxiv.org/abs/2109.06304). We provide [code](https://github.com/sf-wa-326/phrase-bert-topic-model) for training and evaluating Phr... | null | null | null | null | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
6294d63db570e95329148088 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | M-CLIP/XLM-Roberta-Large-Vit-L-14 | M-CLIP | null | 1,530 | 419,395 | False | 2022-05-30T14:35:41Z | 2022-09-15T10:44:59Z | transformers | 14 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json"
] | 40afa80a85e8efa990384a24bbe5a1f6f1cc81b5 | [
"transformers",
"pytorch",
"tf",
"multilingual",
"af",
"sq",
"am",
"ar",
"az",
"bn",
"bs",
"bg",
"ca",
"zh",
"hr",
"cs",
"da",
"nl",
"en",
"et",
"fr",
"de",
"el",
"hi",
"hu",
"is",
"id",
"it",
"ja",
"mk",
"ml",
"mr",
"pl",
"pt",
"ro",
"ru",
"sr... | null | null | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["multilingual", "af", "sq", "am", "ar", "az", "bn", "bs", "bg", "ca", "zh", "hr", "cs", "da", "nl", "en", "et", "fr", "de", "el", "hi", "hu", "is", "id", "it", "ja", "mk", "ml", "mr", "pl", "pt", "ro", "ru", "sr", "sl", "es", "sw", "sv", "tl", "t... | ## Multilingual-clip: XLM-Roberta-Large-Vit-L-14
Multilingual-CLIP extends OpenAI's English text encoders to multiple other languages. This model *only* contains the multilingual text encoder. The corresponding image model `ViT-L-14` can be retrieved via instructions found on OpenAI's [CLIP repository on Github](https... | null | null | null | [
"multilingual",
"af",
"sq",
"am",
"ar",
"az",
"bn",
"bs",
"bg",
"ca",
"zh",
"hr",
"cs",
"da",
"nl",
"en",
"et",
"fr",
"de",
"el",
"hi",
"hu",
"is",
"id",
"it",
"ja",
"mk",
"ml",
"mr",
"pl",
"pt",
"ro",
"ru",
"sr",
"sl",
"es",
"sw",
"sv",
"t... | null | null | null | [
"AutoModel"
] | [
null
] | null | null | null |
64513fe49d916c596e2d190b | 4442c85245f5a070 | 7f171e98bdd0da5f | 83,828 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 380 | seara/rubert-tiny2-russian-emotion-detection-ru-go-emotions | seara | null | 883 | 415,586 | False | 2023-05-02T16:52:52Z | 2024-10-29T14:14:22Z | transformers | 13 | 0 | null | text-classification | {"parameters": {"I64": 2048, "F32": 29202532}, "total": 29204580} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 7435bc383fa97cb8e90486bd96dc8cc55a59063a | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"text-classification",
"sentiment-analysis",
"multi-label-classification",
"sentiment analysis",
"rubert",
"sentiment",
"tiny",
"russian",
"multilabel",
"classification",
"emotion-classification",
"emotion-recognition",... | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["seara/ru_go_emotions"], "eval_results": null, "language": ["ru"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": ["f1", "roc_auc", "precision", "recall"], "model_name": null, "pipeline_tag": "text-classification", "tags": ["sentiment-ana... | This is [RuBERT-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) model fine-tuned for __emotion classification__ of short __Russian__ texts.
The task is a __multi-label classification__ with the following labels:
```yaml
0: admiration
1: amusement
2: anger
3: annoyance
4: approval
5: caring
6: confusion
7: cur... | null | [
"mit"
] | [
"seara/ru_go_emotions"
] | [
"ru"
] | 29,204,580 | null | [
"f1",
"roc_auc",
"precision",
"recall"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65f72c5d1d7d373a9a1e3fd4 | 8e18275abeac16c2 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 522 | suriya7/bart-finetuned-text-summarization | suriya7 | null | 1,213 | 428,328 | False | 2024-03-17T17:46:05Z | 2024-03-24T13:29:28Z | transformers | 9 | 0 | null | summarization | {"parameters": {"F32": 406340696}, "total": 406340696} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | e6d2f3ca885a977326a6015dbfe03c3a1253a3a0 | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"summarization",
"en",
"dataset:EdinburghNLP/xsum",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BartForConditionalGeneration"], "model_type": "bart", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["EdinburghNLP/xsum"], "eval_results": null, "language": ["en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "summarization", "tags": null, "widget": [{"text": "Now, there is no doubt that one o... | # BART Large CNN Text Summarization Model
This model is based on the Facebook BART (Bidirectional and Auto-Regressive Transformers) architecture, specifically the large variant fine-tuned for text summarization tasks. BART is a sequence-to-sequence model introduced by Facebook AI, capable of handling various natural l... | null | [
"mit"
] | [
"EdinburghNLP/xsum"
] | [
"en"
] | 406,340,696 | null | null | [
"bart",
"BartForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67af7046f5d20694b4fbe55d | 6141a952851f5feb | 62b8c2882e6b373c | 51,200 | BPE | 50,939 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 523 | nie3e/go-emotions-polish-gpt2-small-v0.0.1 | nie3e | {
"models": [
{
"_id": "633490303fbd80d9992a69d1",
"id": "sdadas/polish-gpt2-small"
}
],
"relation": "finetune"
} | 21 | 420,320 | False | 2025-02-14T16:33:10Z | 2025-07-22T18:52:51Z | transformers | 0 | 0 | [{"name": "go-emotions-polish-gpt2-small-v0.0.1", "results": []}] | text-classification | {"parameters": {"F32": 125971968}, "total": 125971968} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 5bd28027332095f8cb7d9e7a0fefa2ee33222417 | [
"transformers",
"safetensors",
"gpt2",
"text-classification",
"generated_from_trainer",
"multi-class-classification",
"multi-label-classification",
"emotions",
"pl",
"arxiv:2005.00547",
"base_model:sdadas/polish-gpt2-small",
"base_model:finetune:sdadas/polish-gpt2-small",
"license:mit",
"e... | null | {"architectures": ["GPT2ForSequenceClassification"], "model_type": "gpt2", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": "sdadas/polish-gpt2-small", "datasets": null, "eval_results": [], "language": ["pl"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "go-emotions-polish-gpt2-small-v0.0.1", "pipeline_tag": "text-classification", "tags": ["gener... | null | null | [
"mit"
] | null | [
"pl"
] | 125,971,968 | null | null | [
"gpt2",
"AutoModelForSequenceClassification",
"GPT2ForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66e6d38269d1083dd983900c | f5e7f943c396c76b | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 52 | flowaicom/Flow-Judge-v0.1-AWQ | flowaicom | {
"models": [
{
"_id": "66bfbb1a43a701a837a745ac",
"id": "microsoft/Phi-3.5-mini-instruct"
}
],
"relation": "quantized"
} | 5,572 | 417,831 | False | 2024-09-15T12:30:58Z | 2024-10-09T05:59:56Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"I32": 3623878656, "BF16": 197200896}, "total": 3821079552} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_phi3.py",
"generation_config.json",
"model.safetensors",
"modeling_phi3.py",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | d429c1c3d0577ca9c1d5fba4336b1bd47f343a3a | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"lm-judge",
"evaluation",
"nlp",
"conversational",
"autoawq",
"custom_code",
"en",
"base_model:microsoft/Phi-3.5-mini-instruct",
"base_model:quantized:microsoft/Phi-3.5-mini-instruct",
"license:apache-2.0",
"text-generation-infere... | null | {"architectures": ["Phi3ForCausalLM"], "auto_map": {"AutoConfig": "configuration_phi3.Phi3Config", "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"}, "model_type": "phi3", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{ bos_token }}{% for m... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "microsoft/Phi-3.5-mini-instruct", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy", "f1", "precision", "recall", "pearsonr", "spearmanr", "kendall-tau"], "model_name": "... | # Flow-Judge-v0.1-AWQ
- Original model: [Flow-Judge-v0.1](https://huggingface.co/flowaicom/Flow-Judge-v0.1)
- Model collection: [Flow-Judge-v0.1 models](https://huggingface.co/collections/flowaicom/flow-judge-v01-66e6af5fc3b3a128bde07dec)
- Technical report: [Flow Judge: An Open Small Language Model for LLM System Eval... | null | [
"apache-2.0"
] | null | [
"en"
] | 3,821,079,552 | null | [
"accuracy",
"f1",
"precision",
"recall",
"pearsonr",
"spearmanr",
"kendall-tau"
] | [
"AutoModelForCausalLM",
"phi3",
"Phi3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64b8e0e9e3d41dbd69650391 | eb0cfe5f64b9b175 | 3a0d5827f8e29099 | 42,774 | BPE | 42,510 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 524 | NetherlandsForensicInstitute/robbert-2022-dutch-sentence-transformers | NetherlandsForensicInstitute | {
"models": [
{
"_id": "62fa1674efd2de85492ba4c7",
"id": "DTAI-KULeuven/robbert-2022-dutch-base"
}
],
"relation": "finetune"
} | 12,989 | 489,771 | False | 2023-07-20T07:23:21Z | 2025-05-16T13:11:37Z | sentence-transformers | 14 | 0 | null | sentence-similarity | {"parameters": {"I64": 514, "F32": 118892544}, "total": 118893058} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"merges.txt",
"model.safetensors",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json... | 49e0e19472a527708e62747ffd12091e23bc1980 | [
"sentence-transformers",
"pytorch",
"safetensors",
"roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"nl",
"dataset:NetherlandsForensicInstitute/AllNLI-translated-nl",
"dataset:NetherlandsForensicInstitute/altlex-translated-nl",
"dataset:NetherlandsForensicInstitute/coco-ca... | null | {"architectures": ["RobertaModel"], "model_type": "roberta", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "cls_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": fa... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": ["DTAI-KULeuven/robbert-2022-dutch-base"], "datasets": ["NetherlandsForensicInstitute/AllNLI-translated-nl", "NetherlandsForensicInstitute/altlex-translated-nl", "NetherlandsForensicInstitute/coco-captions-translated-nl", "NetherlandsForensicInstitute/flickr30k-captions-translated-nl", "NetherlandsForens... | # robbert-2022-dutch-sentence-transformers
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
This model is based on [KU Leuven's RobBER... | null | [
"apache-2.0"
] | [
"NetherlandsForensicInstitute/AllNLI-translated-nl",
"NetherlandsForensicInstitute/altlex-translated-nl",
"NetherlandsForensicInstitute/coco-captions-translated-nl",
"NetherlandsForensicInstitute/flickr30k-captions-translated-nl",
"NetherlandsForensicInstitute/msmarco-translated-nl",
"NetherlandsForensicI... | [
"nl"
] | 118,893,058 | null | null | [
"roberta",
"AutoModel",
"RobertaModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
6541f856eccc4f48dce3a705 | 622c3d21644af081 | cad4902422b140fb | 64,000 | BPE | 110,029 | true | false | false | true | 3 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 525 | 01-ai/Yi-34B | 01-ai | null | 10,914 | 464,425 | False | 2023-11-01T07:03:50Z | 2024-11-11T03:31:31Z | transformers | 1,300 | 0 | null | text-generation | {"parameters": {"BF16": 34388917248}, "total": 34388917248} | [
".gitattributes",
"LICENSE",
"README.md",
"Yi.svg",
"config.json",
"generation_config.json",
"md5",
"model-00001-of-00007.safetensors",
"model-00002-of-00007.safetensors",
"model-00003-of-00007.safetensors",
"model-00004-of-00007.safetensors",
"model-00005-of-00007.safetensors",
"model-00006... | e1fa7c83283f2e1d5a12cb4adea37c3f829e28f8 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"arxiv:2403.04652",
"arxiv:2311.16502",
"arxiv:2401.11944",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<|startoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<unk>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "widget": [{"example_title": "Yi-34B-Chat", "text": "hi", "outpu... | - they might want nothing more than destruction itself rather then anything else from their quest after immortality (and maybe someone should tell them about modern medicine)? In any event though – one thing remains true regardless : whether or not success comes easy depends entirely upon how much effort we put into co... | null | [
"apache-2.0"
] | null | null | 34,388,917,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17bac3 | 382b5a4eb98f0296 | d965e4a9140ecf72 | 21,128 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 33 | hfl/rbt6 | hfl | null | 338 | 411,751 | False | 2022-03-02T23:29:05Z | 2021-05-19T19:22:02Z | transformers | 11 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"flax_model.msgpack",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 460e5cea82f393f75495db07da8055a957b53a2c | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"arxiv:1906.08101",
"arxiv:2004.13922",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["bert"]} | # This is a re-trained 6-layer RoBERTa-wwm-ext model.
## Chinese BERT with Whole Word Masking
For further accelerating Chinese natural language processing, we provide **Chinese pre-trained BERT with Whole Word Masking**.
**[Pre-Training with Whole Word Masking for Chinese BERT](https://arxiv.org/abs/1906.08101)**
... | null | [
"apache-2.0"
] | null | [
"zh"
] | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65962671c57a761c568bd49a | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | nomic-ai/nomic-bert-2048 | nomic-ai | null | 3,202 | 431,214 | False | 2024-01-04T03:30:57Z | 2025-04-29T14:25:30Z | transformers | 54 | 0 | null | fill-mask | {"parameters": {"F32": 137323008}, "total": 137323008} | [
".gitattributes",
"README.md",
"config.json",
"configuration_hf_nomic_bert.py",
"model.safetensors",
"modeling_hf_nomic_bert.py",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 7710840340a098cfb869c4f65e87cf2b1b70caca | [
"transformers",
"pytorch",
"safetensors",
"nomic_bert",
"fill-mask",
"custom_code",
"en",
"dataset:wikimedia/wikipedia",
"dataset:bookcorpus",
"dataset:nomic-ai/nomic-bert-2048-pretraining-data",
"arxiv:2104.09864",
"arxiv:2002.05202",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["NomicBertForPreTraining"], "auto_map": {"AutoConfig": "configuration_hf_nomic_bert.NomicBertConfig", "AutoModel": "modeling_hf_nomic_bert.NomicBertModel", "AutoModelForMaskedLM": "modeling_hf_nomic_bert.NomicBertForPreTraining", "AutoModelForSequenceClassification": "modeling_hf_nomic_bert.NomicBert... | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": "modeling_hf_nomic_bert.NomicBertForPreTraining",
"pipeline_tag": "fill-mask",
"processor": null
} | {"base_model": null, "datasets": ["wikimedia/wikipedia", "bookcorpus", "nomic-ai/nomic-bert-2048-pretraining-data"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": nul... | # nomic-bert-2048: A 2048 Sequence Length Pretrained BERT
`nomic-bert-2048` is a BERT model pretrained on `wikipedia` and `bookcorpus` with a max sequence length of 2048.
We make several modifications to our BERT training procedure similar to [MosaicBERT](https://www.databricks.com/blog/mosaicbert).
Namely, we add:
... | null | [
"apache-2.0"
] | [
"wikimedia/wikipedia",
"bookcorpus",
"nomic-ai/nomic-bert-2048-pretraining-data"
] | [
"en"
] | 137,323,008 | null | null | [
"modeling_hf_nomic_bert.NomicBertForPreTraining",
"NomicBertForPreTraining",
"AutoModelForMaskedLM",
"nomic_bert"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
669b299c3197305664148704 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | meta-llama/Llama-3.1-405B-Instruct-FP8 | meta-llama | {
"models": [
{
"_id": "6696baec8fbd2777a1074e07",
"id": "meta-llama/Llama-3.1-405B-Instruct"
}
],
"relation": "quantized"
} | 9,127 | 511,102 | manual | 2024-07-20T03:06:04Z | 2024-09-25T17:02:45Z | transformers | 193 | 0 | null | text-generation | {"parameters": {"BF16": 81314922496, "F32": 15237120, "F8_E4M3": 324538466304}, "total": 405868625920} | [
".gitattributes",
"LICENSE",
"README.md",
"USE_POLICY.md",
"config.json",
"generation_config.json",
"model-00001-of-00109.safetensors",
"model-00002-of-00109.safetensors",
"model-00003-of-00109.safetensors",
"model-00004-of-00109.safetensors",
"model-00005-of-00109.safetensors",
"model-00006-o... | 64a54b704768dfd589a3e4ac05d546052f67f4fd | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"conversational",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"arxiv:2204.05149",
"base_model:meta-llama/Llama-3.1-405B-Instruct",
"base_model:quantized:meta-llama/Llama-3.1... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "fbgemm_fp8"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Meta-Llama-3.1-405B-Instruct", "datasets": null, "eval_results": null, "language": ["en", "de", "fr", "it", "pt", "hi", "es", "th"], "library_name": "transformers", "license": "llama3.1", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-ge... | null | null | [
"llama3.1"
] | null | [
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th"
] | 405,868,625,920 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68122cda7850b4be75df3bfb | aa96894d04e62e93 | 434a6daecf2d6334 | 64,000 | Unigram | null | true | true | true | true | 107 | Sequence | Sequence | Sequence | [
"Prepend",
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 526 | kyutai/helium-1-2b | kyutai | null | 22,536 | 498,322 | False | 2025-04-30T13:59:54Z | 2025-04-30T14:38:01Z | transformers | 53 | 0 | null | text-generation | {"parameters": {"BF16": 2023868416}, "total": 2023868416} | [
".gitattributes",
"README.md",
"config.json",
"helium_sticker.png",
"model.safetensors",
"tokenizer.json",
"tokenizer.model"
] | 5764947fc2e782982c24f363eacd9baea3e821f8 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"bg",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fi",
"fr",
"ga",
"hr",
"hu",
"it",
"lt",
"lv",
"mt",
"nl",
"pl",
"pt",
"ro",
"sk",
"sl",
"sv",
"license:cc-by-sa-4.0",
"text-generation-inference",
... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama"} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["bg", "cs", "da", "de", "el", "en", "es", "et", "fi", "fr", "ga", "hr", "hu", "it", "lt", "lv", "mt", "nl", "pl", "pt", "ro", "sk", "sl", "sv"], "library_name": "transformers", "license": "cc-by-sa-4.0", "license_name": null, "license_link": null... | null | null | [
"cc-by-sa-4.0"
] | null | [
"bg",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fi",
"fr",
"ga",
"hr",
"hu",
"it",
"lt",
"lv",
"mt",
"nl",
"pl",
"pt",
"ro",
"sk",
"sl",
"sv"
] | 2,023,868,416 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
663db2d024d6737844c45530 | 302e00ef85417c9b | 3f3879d485dc5e16 | 63,992 | BPE | 110,029 | true | false | false | true | 231 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"Strip",
"ByteFallback",
"Fuse"
] | 527 | 01-ai/Yi-1.5-9B-Chat | 01-ai | null | 18,917 | 493,704 | False | 2024-05-10T05:38:24Z | 2024-06-26T10:41:03Z | transformers | 148 | 0 | null | text-generation | {"parameters": {"BF16": 8829407232}, "total": 8829407232} | [
".gitattributes",
"NOTICE",
"README.md",
"config.json",
"generation_config.json",
"md5",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
... | 1a0fc698cf883c4f5c325f026ca79f0ebd9955a5 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2403.04652",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|startoftext|>", "chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ system_message }}{% endif %}{% for message in mes... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | <div align="center">
<picture>
<img src="https://raw.githubusercontent.com/01-ai/Yi/main/assets/img/Yi_logo_icon_light.svg" width="150px">
</picture>
</div>
<p align="center">
<a href="https://github.com/01-ai">🐙 GitHub</a> •
<a href="https://discord.gg/hYUwWddeAu">👾 Discord</a> •
<a href="https://twitter... | null | [
"apache-2.0"
] | null | null | 8,829,407,232 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
625057580953e1175c83e895 | 0060aa4b889b944c | 3565054b8b174bb6 | 50,518 | BPE | 50,001 | false | true | true | true | 258 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 528 | facebook/incoder-1B | facebook | null | 1,770 | 435,152 | False | 2022-04-08T15:40:08Z | 2023-01-24T17:06:37Z | transformers | 40 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 1e0e77a92e7a2a30c95da8d24d818122cfc37f7c | [
"transformers",
"pytorch",
"xglm",
"text-generation",
"code",
"python",
"javascript",
"arxiv:2204.05999",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XGLMForCausalLM"], "model_type": "xglm", "tokenizer_config": {"bos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["code", "python", "javascript"]} | # InCoder 1B
A 1B parameter decoder-only Transformer model trained on code using a causal-masked objective, which allows inserting/infilling code as well as standard left-to-right generation.
The model was trained on public open-source repositories with a permissive, non-copyleft, license (Apache 2.0, MIT, BSD-2 or B... | null | [
"cc-by-nc-4.0"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"xglm",
"XGLMForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64c024eb50f0d6578db69baa | 1e7de54e704f366a | d4959f5e45fb7540 | 32,001 | BPE | 61,249 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 309 | NousResearch/Nous-Hermes-llama-2-7b | NousResearch | null | 26,170 | 460,349 | False | 2023-07-25T19:39:23Z | 2024-09-26T13:57:06Z | transformers | 70 | 0 | null | text-generation | {"parameters": {"BF16": 6738415616}, "total": 6738415616} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | cbd525ad0d5012e470c7696d5905345dc082e432 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"llama-2",
"self-instruct",
"distillation",
"synthetic instruction",
"en",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": ["mit"], "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["llama-2", "self-instruct", "distillation", "synthetic instruction"], "new_version": ... | # Model Card: Nous-Hermes-Llama2-7b
Compute provided by our project sponsor Redmond AI, thank you! Follow RedmondAI on Twitter @RedmondAI.
## Model Description
Nous-Hermes-Llama2-7b is a state-of-the-art language model fine-tuned on over 300,000 instructions. This model was fine-tuned by Nous Research, with Teknium ... | null | [
"mit"
] | null | [
"en"
] | 6,738,415,616 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6328ae951558dac67c45d3e1 | 5192a3fbf623fc70 | 3f5617f282b50422 | 30,521 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 529 | firqaaa/indo-sentence-bert-base | firqaaa | null | 11,383 | 459,173 | False | 2022-09-19T18:01:57Z | 2024-03-03T00:02:00Z | sentence-transformers | 22 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | af8d649e60fbd85b6e1dee7649a749a83996304f | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"id",
"arxiv:1908.10084",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["id"], "library_name": "sentence-transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction... | # indo-sentence-bert-base
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes ... | null | [
"apache-2.0"
] | null | [
"id"
] | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
64e785f06e8d01b7998924e3 | 271640fddfc1bd19 | 704a2955bcffd2d4 | 32,016 | BPE | 61,260 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 212 | codellama/CodeLlama-13b-hf | codellama | null | 3,096 | 434,556 | False | 2023-08-24T16:31:44Z | 2024-04-12T14:17:10Z | transformers | 118 | 0 | null | text-generation | {"parameters": {"BF16": 13016028160}, "total": 13016028160} | [
".gitattributes",
"LICENSE",
"README.md",
"USE_POLICY.md",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"pytorch_model-00001-of-00003.bin",
"pytorch_model-000... | 8da65ff4ee20f74ecd107ca9d54f9f121b279860 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"llama-2",
"code",
"arxiv:2308.12950",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["code"], "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["llama-2"]} | # **Code Llama**
Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the base 13B version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding. Links t... | null | [
"llama2"
] | null | [
"code"
] | 13,016,028,160 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17def2 | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | microsoft/layoutlm-base-cased | microsoft | null | 12,057 | 458,137 | False | 2022-03-02T23:29:05Z | 2021-09-27T05:55:31Z | transformers | 19 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 91acf0f93186fbcebb9f80c2e2259754f0ef922b | [
"transformers",
"pytorch",
"layoutlm",
"arxiv:1912.13318",
"endpoints_compatible",
"region:us"
] | null | {"model_type": "layoutlm", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | null | # LayoutLM
**Multimodal (text + layout/format + image) pre-training for document AI**
[Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://aka.ms/layoutlm)
## Model description
LayoutLM is a simple but effective pre-training method of text and layout for document ... | null | null | null | null | null | null | null | [
"layoutlm",
"AutoModel"
] | [
null
] | null | null | null |
63e4b876a26ec2301f07632d | f0b360fada45735d | 8cdfcc055eb9d121 | 32,101 | Unigram | null | true | true | true | true | 104 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 196 | Salesforce/blip2-flan-t5-xxl | Salesforce | null | 3,204 | 426,384 | False | 2023-02-09T09:10:14Z | 2025-02-03T06:35:28Z | transformers | 93 | 0 | null | image-text-to-text | {"parameters": {"F32": 12229596672}, "total": 12229596672} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
"model.safetensors.inde... | 847ce5bfa5c6b374da8f3216c50c64e2142edbed | [
"transformers",
"pytorch",
"safetensors",
"blip-2",
"visual-question-answering",
"vision",
"image-to-text",
"image-captioning",
"image-text-to-text",
"en",
"arxiv:2301.12597",
"arxiv:2210.11416",
"license:mit",
"region:us"
] | null | {"architectures": ["Blip2ForConditionalGeneration"], "model_type": "blip-2", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForVisualQuestionAnswering",
"custom_class": null,
"pipeline_tag": "visual-question-answering",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ["vision", "image-to-text", "image-captioning", "visual-question-answering... | # BLIP-2, Flan T5-xxl, pre-trained only
BLIP-2 model, leveraging [Flan T5-xxl](https://huggingface.co/google/flan-t5-xxl) (a large language model).
It was introduced in the paper [BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models](https://arxiv.org/abs/2301.12597) b... | null | [
"mit"
] | null | [
"en"
] | 12,229,596,672 | null | null | [
"Blip2ForConditionalGeneration",
"AutoModelForVisualQuestionAnswering",
"blip-2"
] | [
"image-text-to-text",
"visual-question-answering",
"image-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text",
"logits"
] |
627f6b26074ef35a954d301d | 91092dd761c2edf6 | 32c99d7cd67fcc7e | 30,873 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 530 | Sigma/financial-sentiment-analysis | Sigma | null | 287 | 408,430 | False | 2022-05-14T08:41:10Z | 2022-05-14T11:48:56Z | transformers | 21 | 0 | [{"name": "financial-sentiment-analysis", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "financial_phrasebank", "type": "financial_phrasebank", "args": "sentences_allagree"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value": 0.9924242424242424, "ver... | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/May14_08-41-28_2a59d5e087ff/1652517746.1369002/events.out.tfevents.1652517746.2a59d5e087ff.72.1",
"runs/May14_08-41-28_2a59d5e087ff/events.out.tfevents.1652517746.2a59d5e087ff.72.0",
"runs/May14_08-57-30_2a59d5e087f... | d78ca172e07e94390f615739cee98a2154381f7e | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:financial_phrasebank",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["financial_phrasebank"], "metrics": ["accuracy", "f1"], "tags": ["generated_from_trainer"], "model-index": [{"name": "financial-sentiment-analysis", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "financial_phrasebank", "type": "financial_phraseban... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# financial-sentiment-analysis
This model is a fine-tuned version of [ahmedrachid/FinancialBERT](https://huggingface.co/ahmedrachid... | null | null | [
"financial_phrasebank"
] | null | null | null | [
"accuracy",
"f1"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f17ee70 | 191e06b04083279c | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 26 | philschmid/tiny-bert-sst2-distilled | philschmid | null | 7,198 | 427,769 | False | 2022-03-02T23:29:05Z | 2022-01-31T18:50:41Z | transformers | 2 | 0 | [{"name": "tiny-bert-sst2-distilled", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "glue", "type": "glue", "args": "sst2"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value": 0.8325688073394495, "verified": false}]}]}] | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 874eb28543ea7a7df80b6158bbf772d203efcab6 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["glue"], "license": "apache-2.0", "metrics": ["accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "tiny-bert-sst2-distilled", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "args": "sst2"}, "metrics": [... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tiny-bert-sst2-distilled
This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/... | null | [
"apache-2.0"
] | [
"glue"
] | null | null | null | [
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64d2a40361b976fdb05d3572 | f916a488a87915ce | d4959f5e45fb7540 | 32,001 | BPE | 61,249 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 531 | togethercomputer/Llama-2-7B-32K-Instruct | togethercomputer | null | 2,413 | 415,077 | False | 2023-08-08T20:22:27Z | 2024-03-28T01:13:47Z | transformers | 160 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"modeling_flash_llama.py",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tok... | d27380af003252f5eb0d218e104938b4e673e3f3 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"en",
"dataset:togethercomputer/llama-instruct",
"arxiv:2307.03172",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<unk>", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["togethercomputer/llama-instruct"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Llama-2-7B-32K-Instruct
## Model Description
Llama-2-7B-32K-Instruct is an open-source, long-context chat model finetuned from [Llama-2-7B-32K](https://huggingface.co/togethercomputer/Llama-2-7B-32K), over high-quality instruction and chat data.
We built Llama-2-7B-32K-Instruct with less than 200 lines of Python sc... | null | [
"llama2"
] | [
"togethercomputer/llama-instruct"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17b612 | ed7b346ae536b711 | 7135f15e02b88987 | 96,103 | Unigram | null | true | true | true | true | 7 | Sequence | Sequence | Metaspace | [
"Precompiled",
"Replace"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 440 | google/bigbird-pegasus-large-bigpatent | google | null | 180 | 407,515 | False | 2022-03-02T23:29:05Z | 2023-01-24T16:36:44Z | transformers | 41 | 0 | null | summarization | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | d76208892930b15ab2f4ea0cc49b8d9f74c352df | [
"transformers",
"pytorch",
"bigbird_pegasus",
"text2text-generation",
"summarization",
"en",
"dataset:big_patent",
"arxiv:2007.14062",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BigBirdPegasusForConditionalGeneration"], "model_type": "bigbird_pegasus", "tokenizer_config": {"pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": fals... | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["big_patent"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["summarization"]} | # BigBirdPegasus model (large)
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
BigBird was int... | null | [
"apache-2.0"
] | [
"big_patent"
] | [
"en"
] | null | null | null | [
"bigbird_pegasus",
"BigBirdPegasusForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6402f7aa66f4a994f1ab62e0 | 160ff155961a6bcb | 95e12a961ee8f7f8 | 197,285 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 532 | l3cube-pune/indic-sentence-bert-nli | l3cube-pune | null | 619 | 410,036 | False | 2023-03-04T07:47:54Z | 2023-06-11T14:59:00Z | sentence-transformers | 2 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | aab1d6a0ace569c670f54173e1b0f0bb607f13c8 | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"multilingual",
"en",
"hi",
"mr",
"kn",
"ta",
"te",
"ml",
"gu",
"or",
"pa",
"bn",
"arxiv:2304.11434",
"arxiv:2211.11187",
"license:cc-by-4.0",
"text-embeddings-inference... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["multilingual", "en", "hi", "mr", "kn", "ta", "te", "ml", "gu", "or", "pa", "bn"], "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity... | # IndicSBERT
This is a MuRIL model (google/muril-base-cased) trained on the NLI dataset of ten major Indian Languages. <br>
The single model works for English, Hindi, Marathi, Kannada, Tamil, Telugu, Gujarati, Oriya, Punjabi, Malayalam, and Bengali.
The model also has cross-lingual capabilities. <br>
Released as a par... | null | [
"cc-by-4.0"
] | null | [
"multilingual",
"en",
"hi",
"mr",
"kn",
"ta",
"te",
"ml",
"gu",
"or",
"pa",
"bn"
] | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
67b5b1d7e5d3a2a80768abf2 | 8f765ac1c479905b | 0bc4a44a6c0c4e50 | 102,400 | Unigram | null | false | true | true | true | 18 | null | Metaspace | Sequence | null | [
"Metaspace"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 533 | sbintuitions/modernbert-ja-70m | sbintuitions | null | 1,025 | 429,302 | False | 2025-02-19T10:26:31Z | 2025-05-01T03:42:41Z | transformers | 6 | 0 | null | fill-mask | {"parameters": {"F32": 70253056}, "total": 70253056} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | ca49e733a062934aef34312f496fea8f4a0beba8 | [
"transformers",
"safetensors",
"modernbert",
"fill-mask",
"ja",
"en",
"arxiv:2412.13663",
"arxiv:2104.09864",
"arxiv:2404.10830",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ModernBertForMaskedLM"], "model_type": "modernbert", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<cls>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "<sep>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ja", "en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "fill-mask", "tags": null} | # ModernBERT-Ja-70M
This repository provides Japanese ModernBERT trained by [SB Intuitions](https://www.sbintuitions.co.jp/).
[ModernBERT](https://arxiv.org/abs/2412.13663) is a new variant of the BERT model that combines local and global attention, allowing it to handle long sequences while maintaining high computat... | null | [
"mit"
] | null | [
"ja",
"en"
] | 70,253,056 | null | null | [
"ModernBertForMaskedLM",
"modernbert",
"AutoModelForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64fe0a4535a7fc7d4f5eb61e | a29994e5588cba89 | afeab537347c7e69 | 32,007 | BPE | 61,249 | true | false | true | true | 10 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 534 | LeoLM/leo-hessianai-7b-chat | LeoLM | null | 1,161 | 411,358 | False | 2023-09-10T18:26:13Z | 2023-10-09T21:30:55Z | transformers | 18 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"modeling_flash_llama.py",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | a4c5fcbaea9f0a04f386533b0331c7f55a84f81c | [
"transformers",
"pytorch",
"llama",
"text-generation",
"conversational",
"custom_code",
"en",
"de",
"dataset:LeoLM/OpenSchnabeltier",
"dataset:OpenAssistant/OASST-DE",
"dataset:FreedomIntelligence/alpaca-gpt4-deutsch",
"dataset:FreedomIntelligence/evol-instruct-deutsch",
"dataset:LeoLM/Germa... | null | {"architectures": ["LlamaForCausalLM"], "auto_map": {"AutoModelForCausalLM": "modeling_flash_llama.LlamaForCausalLM"}, "model_type": "llama", "tokenizer_config": {"bos_token": "<|im_start|>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["LeoLM/OpenSchnabeltier", "OpenAssistant/OASST-DE", "FreedomIntelligence/alpaca-gpt4-deutsch", "FreedomIntelligence/evol-instruct-deutsch", "LeoLM/German_Poems", "LeoLM/German_Songs"], "eval_results": null, "language": ["en", "de"], "library_name": "transformers", "license": null, "lic... | # LAION LeoLM: **L**inguistically **E**nhanced **O**pen **L**anguage **M**odel
Meet LeoLM, the first open and commercially available German Foundation Language Model built on Llama-2.
Our models extend Llama-2's capabilities into German through continued pretraining on a large corpus of German-language and mostly loca... | null | null | [
"LeoLM/OpenSchnabeltier",
"OpenAssistant/OASST-DE",
"FreedomIntelligence/alpaca-gpt4-deutsch",
"FreedomIntelligence/evol-instruct-deutsch",
"LeoLM/German_Poems",
"LeoLM/German_Songs"
] | [
"en",
"de"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65ff57402fb1cc3fecf36892 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | mistral-community/Mistral-7B-v0.2 | mistral-community | null | 6,439 | 433,196 | False | 2024-03-23T22:27:12Z | 2024-07-01T08:55:52Z | transformers | 228 | 0 | null | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.... | 80cf49b18de6354fd8a6d1e81c177dd830e05eea | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | > [!WARNING]
> This model checkpoint is provided as-is and might not be up-to-date. Please use the corresponding version from https://huggingface.co/mistralai org
Conversion process:
1. Download original weights from https://models.mistralcdn.com/mistral-7b-v0-2/mistral-7B-v0.2.tar
2. Convert with https://github.com/... | null | [
"apache-2.0"
] | null | null | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
672f5977b6a16a91f7cdf0d3 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-Coder-14B-Instruct-AWQ | Qwen | {
"models": [
{
"_id": "672b1f9a250205b317ab81e5",
"id": "Qwen/Qwen2.5-Coder-14B-Instruct"
}
],
"relation": "quantized"
} | 357,348 | 1,091,447 | False | 2024-11-09T12:45:43Z | 2025-01-12T02:15:55Z | transformers | 16 | 0 | null | text-generation | {"parameters": {"I32": 13212057600, "F16": 1557976064}, "total": 14770033664} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"... | eb3172f06a6d6b3a15f08947b0668d782e4d2d2c | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"code",
"codeqwen",
"chat",
"qwen",
"qwen-coder",
"conversational",
"en",
"arxiv:2409.12186",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-Coder-14B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-Coder-14B-In... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen2.5-Coder-14B-Instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, ... | # Qwen2.5-Coder-14B-Instruct-AWQ
<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Introduction
Qwen2.5-Coder is the latest series... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct/blob/main/LICENSE"
] | null | [
"en"
] | 14,770,033,664 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
687de260234339fed21e768a | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | Qwen/Qwen3-235B-A22B-Instruct-2507 | Qwen | null | 184,380 | 1,064,329 | False | 2025-07-21T06:46:56Z | 2025-09-17T06:52:55Z | transformers | 770 | 2 | null | text-generation | null | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"config_1m.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00118.safetensors",
"model-00002-of-00118.safetensors",
"model-00003-of-00118.safetensors",
"model-00004-of-00118.safetensors",
"model-00005-of-00118.safetensors",... | ac9c66cc9b46af7306746a9250f23d47083d689e | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"conversational",
"arxiv:2402.17463",
"arxiv:2407.02490",
"arxiv:2501.15383",
"arxiv:2404.06654",
"arxiv:2505.09388",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generati... | # Qwen3-235B-A22B-Instruct-2507
<a href="https://chat.qwen.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Highlights
We introduce the updated version of the... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507/blob/main/LICENSE"
] | null | null | null | null | null | [
"qwen3_moe",
"AutoModelForCausalLM",
"Qwen3MoeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67ff92c1a93c489f94ab29c6 | b647996d6543f730 | 7ab62ce4e32550df | 151,674 | BPE | 151,387 | true | true | true | true | 31 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 172 | OpenGVLab/InternVL3-1B-Instruct | OpenGVLab | {
"models": [
{
"_id": "6800a6012522e96be1eb6010",
"id": "OpenGVLab/InternVL3-1B-Pretrained"
}
],
"relation": "finetune"
} | 2,517 | 424,407 | False | 2025-04-16T11:21:37Z | 2025-09-11T12:49:48Z | transformers | 9 | 0 | null | image-text-to-text | {"parameters": {"BF16": 938193024}, "total": 938193024} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_intern_vit.py",
"configuration_internvl_chat.py",
"conversation.py",
"examples/image1.jpg",
"examples/image2.jpg",
"examples/red-panda.mp4",
"generation_config.json",
"merges.txt",
"model.safetensors",
"model... | f91c6391476dbc8fd07674d2589e8168d3ca667f | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"internvl",
"custom_code",
"image-text-to-text",
"conversational",
"multilingual",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.10442",
"arxiv:2504.10479",
"arxiv:2412.09616",
"base_model:O... | null | {"architectures": ["InternVLChatModel"], "auto_map": {"AutoConfig": "configuration_internvl_chat.InternVLChatConfig", "AutoModel": "modeling_internvl_chat.InternVLChatModel", "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel"}, "model_type": "internvl_chat", "tokenizer_config": {"bos_token": null, "chat... | {
"auto_model": "AutoModel",
"custom_class": "modeling_internvl_chat.InternVLChatModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["OpenGVLab/InternVL3-1B-Pretrained"], "datasets": null, "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "apache-2.0", "license_name": "qwen", "license_link": "https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE", "metrics": null, "model_name"... | # InternVL3-1B-Instruct
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggingface... | null | [
"apache-2.0",
"qwen",
"https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE"
] | null | [
"multilingual"
] | 938,193,024 | null | null | [
"AutoModel",
"internvl_chat",
"InternVLChatModel",
"modeling_internvl_chat.InternVLChatModel"
] | [
"image-text-to-text",
"feature-extraction"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text",
"embeddings"
] |
635ada61f9a004065f323392 | 7469dded5408219b | d3a5589134b292ff | 250,100 | Unigram | null | true | true | true | true | 3 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 535 | bigscience/mt0-small | bigscience | null | 1,923 | 424,386 | False | 2022-10-27T19:22:09Z | 2023-09-26T09:16:55Z | transformers | 31 | 0 | [{"name": "mt0-small", "results": [{"task": {"type": "Coreference resolution"}, "dataset": {"type": "winogrande", "name": "Winogrande XL (xl)", "config": "xl", "split": "validation", "revision": "a80f460359d1e9a67c006011c94de42a8759430c"}, "metrics": [{"type": "Accuracy", "value": 50.51, "verified": false}]}, {"task": ... | text-generation | {"parameters": {"F32": 300176768}, "total": 300176768} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"onnx/config.json",
"onnx/decoder_model.onnx",
"onnx/decoder_model_merged.onnx",
"onnx/decoder_with_past_model.onnx",
"onnx/encoder_model.onnx",
"onnx/generation_config.json",
"onnx/special_tokens_map.json",
"onnx/spiece.model"... | 8116a34237e19160ec003147e758f065876d95f0 | [
"transformers",
"pytorch",
"onnx",
"safetensors",
"mt5",
"text2text-generation",
"af",
"am",
"ar",
"az",
"be",
"bg",
"bn",
"ca",
"ceb",
"co",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fil",
"fr",
"fy",
"ga",
"gd",
"gl",... | null | {"architectures": ["MT5ForConditionalGeneration"], "model_type": "mt5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["bigscience/xP3", "mc4"], "language": ["af", "am", "ar", "az", "be", "bg", "bn", "ca", "ceb", "co", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fil", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "haw", "hi", "hmn", "ht", "hu", "hy", "ig", "is", "it", "iw", "ja", "jv", "ka", "kk",... | 
# Table of Contents
1. [Model Summary](#model-summary)
2. [Use](#use)
3. [Limitations](#limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
7. [Citation](#citation)
# Model Summary
> We present BLOOMZ & mT0, a ... | null | [
"apache-2.0"
] | [
"bigscience/xP3",
"mc4"
] | [
"af",
"am",
"ar",
"az",
"be",
"bg",
"bn",
"ca",
"ceb",
"co",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fil",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha",
"haw",
"hi",
"hmn",
"ht",
"hu",
"hy",
"ig",
"is",
"it",
... | 300,176,768 | null | null | [
"mt5",
"MT5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17bac1 | 382b5a4eb98f0296 | d965e4a9140ecf72 | 21,128 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 33 | hfl/rbt3 | hfl | null | 5,381 | 427,756 | False | 2022-03-02T23:29:05Z | 2021-05-19T19:19:45Z | transformers | 39 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"flax_model.msgpack",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 0aa0527ff4170f29e1dfd3eb6ef60dc67e1bf75c | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"arxiv:1906.08101",
"arxiv:2004.13922",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "fill-mask", "tags": ["bert"]} | # This is a re-trained 3-layer RoBERTa-wwm-ext model.
## Chinese BERT with Whole Word Masking
For further accelerating Chinese natural language processing, we provide **Chinese pre-trained BERT with Whole Word Masking**.
**[Pre-Training with Whole Word Masking for Chinese BERT](https://arxiv.org/abs/1906.08101)**
... | null | [
"apache-2.0"
] | null | [
"zh"
] | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66a0371c5c5e2a42a2f09222 | ba8202ef2c1107f0 | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 160 | ibm-ai-platform/llama-160m-accelerator | ibm-ai-platform | null | 850 | 404,816 | False | 2024-07-23T23:05:00Z | 2024-07-24T20:56:55Z | transformers | 1 | 0 | null | null | {"parameters": {"F16": 199497728}, "total": 199497728} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 62caecb70a21d3c97dba0c7c3df4284cfb021f5b | [
"transformers",
"safetensors",
"mlp_speculator",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MLPSpeculatorPreTrainedModel"], "model_type": "mlp_speculator", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | ## Installation from source
```bash
git clone https://github.com/foundation-model-stack/fms-extras
cd fms-extras
pip install -e .
```
## Description
This model is intended to be used as an accelerator for [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) and takes inspiration
from the Medusa specul... | null | [
"apache-2.0"
] | null | null | 199,497,728 | null | null | [
"MLPSpeculatorPreTrainedModel",
"AutoModel",
"mlp_speculator"
] | [
null
] | null | null | null |
66a0cd561b76d29075ef8e8c | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | NousResearch/Meta-Llama-3.1-70B-Instruct | NousResearch | null | 2,425 | 412,506 | False | 2024-07-24T09:45:58Z | 2024-07-24T09:56:26Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"LICENSE",
"README.md",
"USE_POLICY.md",
"config.json",
"generation_config.json",
"model-00001-of-00030.safetensors",
"model-00002-of-00030.safetensors",
"model-00003-of-00030.safetensors",
"model-00004-of-00030.safetensors",
"model-00005-of-00030.safetensors",
"model-00006-o... | d50656ee28e2c2906d317cbbb6fcb55eb4055a84 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"conversational",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"arxiv:2204.05149",
"license:llama3.1",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure"... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "de", "fr", "it", "pt", "hi", "es", "th"], "library_name": "transformers", "license": "llama3.1", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["facebook", "meta... | ## Model Information
The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue us... | null | [
"llama3.1"
] | null | [
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th"
] | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
667da10ecbf90106764a195f | 54895f2d8faef315 | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | true | true | true | 249 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 50 | unsloth/gemma-2-9b-bnb-4bit | unsloth | {
"models": [
{
"_id": "667929f68cc4b2af1e8ad9de",
"id": "google/gemma-2-9b"
}
],
"relation": "quantized"
} | 11,416 | 458,478 | False | 2024-06-27T17:27:42Z | 2025-07-22T11:15:05Z | transformers | 31 | 0 | null | text-generation | {"parameters": {"F32": 588000, "BF16": 918109696, "U8": 8583810440}, "total": 9502508136} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 9ac7aefcf0888216f90f95bf4f63c46517680e18 | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"unsloth",
"gemma",
"google",
"en",
"base_model:google/gemma-2-9b",
"base_model:quantized:google/gemma-2-9b",
"license:gemma",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"deploy:azure",
"re... | null | {"architectures": ["Gemma2ForCausalLM"], "model_type": "gemma2", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "google/gemma-2-9b", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "transformers", "gemma2", "gemma", "google"]} | null | null | [
"gemma"
] | null | [
"en"
] | 9,502,508,136 | null | null | [
"AutoModelForCausalLM",
"gemma2",
"Gemma2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67b3a28f287b14dc152f8d32 | 5913c555399afcb0 | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | true | true | true | 249 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 147 | google/siglip2-so400m-patch16-256 | google | null | 44,955 | 545,281 | False | 2025-02-17T20:56:47Z | 2025-02-21T04:04:01Z | transformers | 1 | 0 | null | zero-shot-image-classification | {"parameters": {"F32": 1135670962}, "total": 1135670962} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"preprocessor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | e8708ab72d125807e45b36fb7d4e0aacbb59f379 | [
"transformers",
"safetensors",
"siglip",
"vision",
"zero-shot-image-classification",
"arxiv:2502.14786",
"arxiv:2303.15343",
"arxiv:2209.06794",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"model_type": "siglip", "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Convers... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "zero-shot-image-classification", "tags": ["vision"], "widget": [{"src": "https://huggi... | null | null | [
"apache-2.0"
] | null | null | 1,135,670,962 | null | null | [
"AutoModel",
"siglip"
] | [
null,
"zero-shot-image-classification"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"logits"
] |
621ffdc136468d709f17a214 | da443ce982f05a4c | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 51 | cross-encoder/msmarco-MiniLM-L12-en-de-v1 | cross-encoder | {
"models": [
{
"_id": "621ffdc136468d709f17decb",
"id": "microsoft/Multilingual-MiniLM-L12-H384"
}
],
"relation": "quantized"
} | 4,450 | 485,452 | False | 2022-03-02T23:29:05Z | 2025-04-15T07:53:17Z | sentence-transformers | 6 | 0 | null | text-ranking | {"parameters": {"I64": 512, "F32": 117654145}, "total": 117654657} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"onnx/model.onnx",
"onnx/model_O1.onnx",
"onnx/model_O2.onnx",
"onnx/model_O3.onnx",
"onnx/model_O4.onnx",
"onnx/model_qint8_arm64.onnx",
"onnx/model_qint8_avx512.onnx",
"onnx/model_qint8_avx512_vnni.onnx",
"onnx/model_quint8... | 6956d9226bd4adaf96a383bcbc5ab61acf4a4b7e | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"openvino",
"bert",
"text-classification",
"transformers",
"text-ranking",
"en",
"de",
"dataset:sentence-transformers/msmarco",
"base_model:microsoft/Multilingual-MiniLM-L12-H384",
"base_model:quantized:microsoft/Multilingual-MiniL... | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normal... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": ["microsoft/Multilingual-MiniLM-L12-H384"], "datasets": ["sentence-transformers/msmarco"], "eval_results": null, "language": ["en", "de"], "library_name": "sentence-transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "te... | null | null | [
"apache-2.0"
] | [
"sentence-transformers/msmarco"
] | [
"en",
"de"
] | 117,654,657 | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-ranking",
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f176b7f | 128f4d40fdb1ae99 | 82ae3e9dca39a0cc | 32,005 | BPE | 66,688 | true | true | true | true | 7 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 301 | Musixmatch/umberto-commoncrawl-cased-v1 | Musixmatch | null | 11,803 | 474,004 | False | 2022-03-02T23:29:04Z | 2021-02-12T11:31:59Z | transformers | 18 | 1 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"tokenizer.json"
] | fe7b14808cccbbe2984b05e6fbfd71127f11008f | [
"transformers",
"pytorch",
"camembert",
"fill-mask",
"it",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["CamembertForMaskedLM"], "model_type": "camembert"} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "it", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # UmBERTo Commoncrawl Cased
[UmBERTo](https://github.com/musixmatchresearch/umberto) is a Roberta-based Language Model trained on large Italian Corpora and uses two innovative approaches: SentencePiece and Whole Word Masking. Now available at [github.com/huggingface/transformers](https://huggingface.co/Musixmatch/umbe... | null | null | null | [
"it"
] | null | null | null | [
"CamembertForMaskedLM",
"AutoModelForMaskedLM",
"camembert"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6612b9822e06cc21934b21e3 | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 106 | TechxGenus/gemma-1.1-2b-it-GPTQ | TechxGenus | null | 20,459 | 484,753 | False | 2024-04-07T15:19:30Z | 2024-04-07T15:52:28Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"I32": 1981808640, "F16": 1049361408}, "total": 3031170048} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"quantize_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 01983793340eb507a77293fdd4275c8641df3203 | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"conversational",
"arxiv:2312.11805",
"arxiv:2009.03300",
"arxiv:1905.07830",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1905.10044",
"arxiv:1907.10641",
"arxiv:1811.00937",
"arxiv:1809.02789",
"arxiv:1911.01547",
"arxiv:17... | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in me... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"messages": [{"role": "user", "content": "How does the brain... | GPTQ quantized version of gemma-1.1-2b-it model.
---
# Gemma Model Card
**Model Page**: [Gemma](https://ai.google.dev/gemma/docs)
This model card corresponds to the latest 2B instruct version of the Gemma model. Here you can find other models in the Gemma family:
| | Base ... | null | [
"gemma"
] | null | null | 3,031,170,048 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
680f7c717ea5fcf6b346bf7a | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | chancharikm/qwen2.5-vl-7b-cam-motion | chancharikm | {
"models": [
{
"_id": "6795ffcd88cd7c0294702a72",
"id": "Qwen/Qwen2.5-VL-7B-Instruct"
}
],
"relation": "finetune"
} | 1,403 | 403,243 | False | 2025-04-28T13:02:41Z | 2025-09-19T12:03:42Z | transformers | 17 | 0 | [{"name": "bal_imb_cap_full_lr2e-4_epoch10.0_freezevisTrue_fps8", "results": []}] | video-text-to-text | {"parameters": {"BF16": 8292166656}, "total": 8292166656} | [
".gitattributes",
"README.md",
"added_tokens.json",
"all_results.json",
"chat_template.json",
"config.json",
"eval_results.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-o... | b37e7f97702c382e3a1ce5c89279ed0f4c174baa | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"llama-factory",
"full",
"generated_from_trainer",
"video-text-to-text",
"arxiv:2404.01291",
"arxiv:2504.15376",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:other",
... | null | {"architectures": ["Qwen2_5_VLForConditionalGeneration"], "model_type": "qwen2_5_vl", "processor_config": {"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a h... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": "Qwen/Qwen2.5-VL-7B-Instruct", "datasets": null, "eval_results": [], "language": null, "library_name": "transformers", "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": "bal_imb_cap_full_lr2e-4_epoch10.0_freezevisTrue_fps8", "pipeline_tag": "video-text-to-text... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
## Model description
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7... | null | [
"other"
] | null | null | 8,292,166,656 | null | null | [
"qwen2_5_vl",
"AutoModelForImageTextToText",
"Qwen2_5_VLForConditionalGeneration"
] | [
"image-text-to-text",
"video-text-to-text"
] | [
"vision",
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
66056356d0703e48e20834fe | d3e093d5df2ac186 | 5c23ae65406ceec5 | 65,536 | BPE | 139,274 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 536 | ai21labs/Jamba-v0.1 | ai21labs | null | 1,704 | 407,293 | False | 2024-03-28T12:32:22Z | 2024-09-11T17:29:22Z | transformers | 1,190 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"configuration_jamba.py",
"generation_config.json",
"model-00001-of-00021.safetensors",
"model-00002-of-00021.safetensors",
"model-00003-of-00021.safetensors",
"model-00004-of-00021.safetensors",
"model-00005-of-00021.safetensors",
"model-00006-of-00... | 9efd11575ba791d9e3d25d4c8b670e78506b2df7 | [
"transformers",
"safetensors",
"jamba",
"text-generation",
"mamba",
"moe",
"custom_code",
"arxiv:2403.19887",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["JambaForCausalLM"], "auto_map": {"AutoConfig": "configuration_jamba.JambaConfig", "AutoModel": "modeling_jamba.JambaModel", "AutoModelForCausalLM": "modeling_jamba.JambaForCausalLM", "AutoModelForSequenceClassification": "model.JambaForSequenceClassification"}, "model_type": "jamba", "tokenizer_conf... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["jamba", "mamba", "moe"]} | This is the base version of the Jamba model. We’ve since released a better, instruct-tuned version, [Jamba-1.5-Mini](https://huggingface.co/ai21labs/AI21-Jamba-1.5-Mini). For even greater performance, check out the scaled-up [Jamba-1.5-Large](https://huggingface.co/ai21labs/AI21-Jamba-1.5-Large).
# Model Card for Jamb... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"jamba",
"JambaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6838616abb5ff3845381807e | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | Qwen/Qwen3-Reranker-8B | Qwen | {
"models": [
{
"_id": "680f0c3e6eacf22a04ee1219",
"id": "Qwen/Qwen3-8B-Base"
}
],
"relation": "finetune"
} | 201,800 | 1,638,009 | False | 2025-05-29T13:30:18Z | 2025-06-09T05:59:48Z | transformers | 216 | 1 | null | text-ranking | {"parameters": {"BF16": 8188548096}, "total": 8188548096} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
"model.safetensors.index.json"... | 5fa94080caafeaa45a15d11f969d7978e087a3db | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"text-ranking",
"arxiv:2506.05176",
"base_model:Qwen/Qwen3-8B-Base",
"base_model:finetune:Qwen/Qwen3-8B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may call o... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen3-8B-Base"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-ranking", "tags": null} | # Qwen3-Reranker-8B
<p align="center">
<img src="https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/logo_qwen3.png" width="400"/>
<p>
## Highlights
The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon ... | null | [
"apache-2.0"
] | null | null | 8,188,548,096 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-ranking",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"logits",
"text"
] |
63a25994f30c46422789cd43 | 30094a1eabdbef67 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 4 | robowaifudev/megatron-gpt2-345m | robowaifudev | null | 5,175 | 423,945 | False | 2022-12-21T00:55:48Z | 2023-04-08T22:07:20Z | transformers | 9 | 0 | [{"name": "megatron-gpt2-345m", "results": [{"task": {"type": "text-generation", "name": "Text generation"}, "dataset": {"name": "WikiText-103", "type": "wikitext"}, "metrics": [{"type": "wikitext", "value": 19.31, "name": "Perplexity", "verified": false}]}, {"task": {"type": "text-generation", "name": "Text generation... | text-generation | {"parameters": {"F16": 354823168, "U8": 25165824}, "total": 379988992} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"tokenizer.json",
"vocab.json"
] | b39f8d00fb9f33da4271be2035da848da896a23b | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"en",
"dataset:wikitext",
"dataset:openwebtext",
"dataset:spacemanidol/cc-stories",
"arxiv:1909.08053",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region... | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2"} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["wikitext", "openwebtext", "spacemanidol/cc-stories"], "language": ["en"], "license": "apache-2.0", "tags": ["gpt2"], "widget": [{"text": "It was a bright cold day in April, and the clocks were striking thirteen. Winston Smith,"}], "model-index": [{"name": "megatron-gpt2-345m", "results": [{"task": {"type... | <!---
# ##############################################################################################
#
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... | null | [
"apache-2.0"
] | [
"wikitext",
"openwebtext",
"spacemanidol/cc-stories"
] | [
"en"
] | 379,988,992 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175df8 | f68a233b6e1cafdd | 7a200ecd99c055f3 | 42,000 | WordPiece | null | true | true | true | true | 110 | Sequence | BertPreTokenizer | WordPiece | [
"Replace",
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 247 | HooshvareLab/bert-fa-zwnj-base | HooshvareLab | null | 76 | 408,505 | False | 2022-03-02T23:29:04Z | 2021-05-18T21:05:42Z | transformers | 18 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 3880fac085e1a338e9564907cba0adeb9e14bc72 | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"fa",
"arxiv:2005.12515",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ParsBERT (v3.0)
A Transformer-based Model for Persian Language Understanding
The new version of BERT v3.0 for Persian is available today and can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Introduction
Pars... | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17433a | 634a9186a6003172 | 5f9f736c7dc6fbfa | 28,996 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 8 | google-bert/bert-large-cased-whole-word-masking | google-bert | null | 498 | 401,133 | False | 2022-03-02T23:29:04Z | 2024-04-10T09:56:46Z | transformers | 23 | 0 | null | fill-mask | {"parameters": {"F32": 334661958}, "total": 334661958} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 4110364c3591c4609a3401e86f6c03a0495536fa | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # BERT large model (cased) whole word masking
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is cased: it makes a diff... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 334,661,958 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17432e | a3d54d6c1d5c62b4 | f87d7bfce4fd9617 | 30,000 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Replace",
"Replace",
"NFKD",
"StripAccents",
"Lowercase",
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 12 | albert/albert-xxlarge-v1 | albert | null | 751 | 403,015 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:01:42Z | transformers | 5 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | 43129068ee5f6a481c148daeac11cc593b8ff440 | [
"transformers",
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT XXLarge v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not ma... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | null | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f1802a6 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | sentence-transformers/bert-large-nli-stsb-mean-tokens | sentence-transformers | null | 6,027 | 415,148 | False | 2022-03-02T23:29:05Z | 2025-03-06T13:33:58Z | sentence-transformers | 3 | 0 | null | sentence-similarity | {"parameters": {"I64": 512, "F32": 335141888}, "total": 335142400} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"onnx/model.onnx",
"onnx/model_O1.onnx",
"onnx/model_O2.onnx",
"onnx/model_O3.onnx",
"onnx/model_O4.onnx",
"onnx/model_qint8_arm64.onnx",
"onnx/m... | 4088dbef2070e7bf5a18e9881698709d2b6f4050 | [
"sentence-transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"openvino",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "sentence-transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction",... | **⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net - Pretrained Models](https://www.sbert.net/docs/pretrained_models.html)**
# sentence-transformers/bert-large-nli-stsb-mean-tokens
This is a [senten... | null | [
"apache-2.0"
] | null | null | 335,142,400 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
623d96881f63e259e899d0b9 | 5b8a6156b5b6e013 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 37 | ml6team/keyphrase-extraction-distilbert-openkp | ml6team | null | 13 | 397,448 | False | 2022-03-25T10:16:40Z | 2023-05-06T08:49:45Z | transformers | 3 | 0 | [{"name": "DeDeckerThomas/keyphrase-extraction-distilbert-openkp", "results": [{"task": {"type": "keyphrase-extraction", "name": "Keyphrase Extraction"}, "dataset": {"type": "midas/openkp", "name": "openkp"}, "metrics": [{"type": "F1 (Seqeval)", "value": 0.43, "name": "F1 (Seqeval)", "verified": false}, {"type": "F1@M"... | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | a40e3bd07a8bba5681d57cc027c5493cd0cafaad | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"keyphrase-extraction",
"en",
"dataset:midas/openkp",
"arxiv:1911.02671",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["midas/openkp"], "language": "en", "license": "mit", "metrics": ["seqeval"], "tags": ["keyphrase-extraction"], "widget": [{"text": "Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document. Thanks to these keyphrases humans can understand the content... | # 🔑 Keyphrase Extraction Model: distilbert-openkp
Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document. Thanks to these keyphrases humans can understand the content of a text very quickly and easily without reading it completely. Keyphrase extraction was first... | null | [
"mit"
] | [
"midas/openkp"
] | [
"en"
] | null | null | [
"seqeval"
] | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
680f92583a9442430aac51ff | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | Qwen/Qwen3-235B-A22B-FP8 | Qwen | {
"models": [
{
"_id": "680daa4ac41c05ba341b67d1",
"id": "Qwen/Qwen3-235B-A22B"
}
],
"relation": "quantized"
} | 41,408 | 517,609 | False | 2025-04-28T14:36:08Z | 2025-07-26T03:46:22Z | transformers | 90 | 0 | null | text-generation | {"parameters": {"F32": 1309010944, "F8_E4M3": 233798893568}, "total": 235107904512} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00048.safetensors",
"model-00002-of-00048.safetensors",
"model-00003-of-00048.safetensors",
"model-00004-of-00048.safetensors",
"model-00005-of-00048.safetensors",
"model-00006-of-0... | 39eb2b067ea6b8e3e1dd97d3cd0c7ffeaf3e1a35 | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"conversational",
"arxiv:2309.00071",
"arxiv:2505.09388",
"base_model:Qwen/Qwen3-235B-A22B",
"base_model:quantized:Qwen/Qwen3-235B-A22B",
"license:apache-2.0",
"endpoints_compatible",
"fp8",
"region:us"
] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "quantization_config": {"quant_method": "fp8"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen3-235B-A22B"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-235B-A22B-FP8/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "tex... | null | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-235B-A22B-FP8/blob/main/LICENSE"
] | null | null | 235,107,904,512 | null | null | [
"qwen3_moe",
"AutoModelForCausalLM",
"Qwen3MoeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66c240885bdd611f9a4117a3 | 54895f2d8faef315 | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | true | true | true | 249 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 50 | zake7749/gemma-2-2b-it-chinese-kyara-dpo | zake7749 | {
"models": [
{
"_id": "669650bb11dbbf600cf4dcf0",
"id": "google/gemma-2-2b-it"
}
],
"relation": "finetune"
} | 47 | 397,418 | False | 2024-08-18T18:42:16Z | 2024-10-28T12:21:29Z | transformers | 15 | 0 | [{"name": "gemma-2-2b-it-chinese-kyara-dpo", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "HuggingFaceH4/ifeval", "args": {"num_few_shot": 0}}, "metrics": [{"type": "inst_level_strict_acc and prompt_level_strict_acc", "value": 53.82, "name":... | text-generation | {"parameters": {"F32": 2614341888}, "total": 2614341888} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00001-of-00003.safetensors",
"model-00002-of-00002.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tok... | 2ca8e31c1587a53aa662ca8a676d2cf5499d4157 | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"conversational",
"zh",
"en",
"dataset:zake7749/kyara-chinese-math-sft-s0-30K",
"dataset:zake7749/kyara-chinese-preference-rl-dpo-s0-30K",
"dataset:zake7749/chinese-sft-stem-zh-hant",
"dataset:zake7749/chinese-sft-stem-zh-hans",
"arxi... | null | {"architectures": ["Gemma2ForCausalLM"], "model_type": "gemma2", "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["google/gemma-2-2b-it"], "datasets": ["zake7749/kyara-chinese-math-sft-s0-30K", "zake7749/kyara-chinese-preference-rl-dpo-s0-30K", "zake7749/chinese-sft-stem-zh-hant", "zake7749/chinese-sft-stem-zh-hans"], "language": ["zh", "en"], "library_name": "transformers", "license": "gemma", "model-index": [{"na... | # Kyara: Knowledge Yielding Adaptive Retrieval Augmentation for LLM Fine-tuning
[](https://zenodo.org/badge/latestdoi/844304447)
<p align="left">
🤗 <a href="https://huggingface.co/zake7749/gemma-2-2b-it-chinese-kyara-dpo">Hugging Face</a> ｜ 🚀<a href="https://g... | null | [
"gemma"
] | [
"zake7749/kyara-chinese-math-sft-s0-30K",
"zake7749/kyara-chinese-preference-rl-dpo-s0-30K",
"zake7749/chinese-sft-stem-zh-hant",
"zake7749/chinese-sft-stem-zh-hans"
] | [
"zh",
"en"
] | 2,614,341,888 | null | null | [
"AutoModelForCausalLM",
"gemma2",
"Gemma2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6704ec589f54b324e07db24d | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | Bllossom/llama-3.2-Korean-Bllossom-3B | Bllossom | null | 1,872 | 421,781 | False | 2024-10-08T08:24:56Z | 2024-12-16T04:42:08Z | transformers | 191 | 0 | null | text-generation | {"parameters": {"BF16": 3212749824}, "total": 3212749824} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | e68fbb0d9c2a4031b0d61b14014eac1a4810ac2e | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"en",
"ko",
"arxiv:2403.10882",
"arxiv:2403.11399",
"license:llama3.2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["meta-llama/Meta-Llama-3.2-3B"], "datasets": null, "eval_results": null, "language": ["en", "ko"], "library_name": "transformers", "license": "llama3.2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | <a href="https://github.com/MLP-Lab/Bllossom">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64a90711c05da19ca834f690/a0VE5UCY1HCEhaHtp3mGa.png" alt="image" width="30%" height="30%">
</a>
# Update!
* [2024.12.06] 훨씬 강력한 최신 Bllossom-AICA-5B로 업데이트 되었습니다 [링크](https://huggingface.co/Bllossom/llama-3.2-... | null | [
"llama3.2"
] | null | [
"en",
"ko"
] | 3,212,749,824 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64f1a7d69d8baeb62eaa1ce4 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | TinyLlama/TinyLlama-1.1B-step-50K-105b | TinyLlama | null | 15,365 | 467,600 | False | 2023-09-01T08:59:02Z | 2023-09-16T03:06:11Z | transformers | 134 | 0 | null | text-generation | {"parameters": {"F32": 1100048384}, "total": 1100048384} | [
".gitattributes",
"README.md",
"TinyLlama_logo.png",
"config.json",
"generation_config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | ae666e2718bf72a193f12e082beb58acc284231d | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:cerebras/SlimPajama-627B",
"dataset:bigcode/starcoderdata",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": false, "rstrip... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["cerebras/SlimPajama-627B", "bigcode/starcoderdata"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | <div align="center">
# TinyLlama-1.1B
</div>
https://github.com/jzhang38/TinyLlama
The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion tokens**. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs 🚀🚀. The training has started on 2023-0... | null | [
"apache-2.0"
] | [
"cerebras/SlimPajama-627B",
"bigcode/starcoderdata"
] | [
"en"
] | 1,100,048,384 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6335a6689dd6d8e9c3a10811 | 37a448cdaece52c8 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 537 | SCUT-DLVCLab/lilt-roberta-en-base | SCUT-DLVCLab | null | 43,037 | 606,040 | False | 2022-09-29T14:06:32Z | 2023-08-31T07:59:36Z | transformers | 20 | 0 | null | feature-extraction | {"parameters": {"I64": 514, "F32": 130755008}, "total": 130755522} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 96328faae824978e47bd0e8ea09f66b85efda5f5 | [
"transformers",
"pytorch",
"safetensors",
"lilt",
"feature-extraction",
"vision",
"arxiv:2202.13669",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LiltModel"], "model_type": "lilt", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "cls_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["vision"]} | # LiLT-RoBERTa (base-sized model)
Language-Independent Layout Transformer - RoBERTa model by stitching a pre-trained RoBERTa (English) and a pre-trained Language-Independent Layout Transformer (LiLT) together. It was introduced in the paper [LiLT: A Simple yet Effective Language-Independent Layout Transformer for Str... | null | [
"mit"
] | null | null | 130,755,522 | null | null | [
"LiltModel",
"AutoModel",
"lilt"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
678e9a65be231faa35cf1e7d | 36935258f89e8e9e | 83d37c6e8ee56b77 | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 315 | Valdemardi/DeepSeek-R1-Distill-Qwen-32B-AWQ | Valdemardi | {
"models": [
{
"_id": "678e15048143a819dd01a3c1",
"id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
}
],
"relation": "quantized"
} | 11,938 | 422,325 | False | 2025-01-20T18:48:05Z | 2025-01-20T20:25:52Z | transformers | 37 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"figures/benchmark.jpg",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_tokens_map.jso... | 1de6a3f7b151f6ea0f6d42acb3566e094eb8a264 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"awq",
"dep... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "base_model_relation": "qua... | # DeepSeek-R1
## Quantization Details
This quantized model was created using AutoAWQ version 3.2.7.post3 with `quant_config`:
```
{
"zero_point": True,
"q_group_size": 128,
"w_bit": 4,
"version": "GEMM"
}
```
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-dis... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6508c16eabdde5290e606c80 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | TheBloke/Llama-2-7B-Chat-AWQ | TheBloke | {
"models": [
{
"_id": "64b02a230c8415cd4a159fff",
"id": "meta-llama/Llama-2-7b-chat-hf"
}
],
"relation": "quantized"
} | 5,093 | 410,508 | False | 2023-09-18T21:30:22Z | 2023-11-09T18:21:14Z | transformers | 24 | 0 | null | text-generation | {"parameters": {"I32": 6476005376, "F16": 262410240}, "total": 6738415616} | [
".gitattributes",
"LICENSE.txt",
"Notice",
"README.md",
"USE_POLICY.md",
"config.json",
"generation_config.json",
"model.safetensors",
"quant_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | ee91097dc818c742d9b648147891dfadd9638ace | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-2",
"en",
"arxiv:2307.09288",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"base_model:quantized:meta-llama/Llama-2-7b-chat-hf",
"license:llama2",
"text-generation-inference",
"4-bit",
"awq"... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "awq", "bits": 4}, "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "cont... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Llama-2-7b-chat-hf", "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": "Llama 2 7B Chat", "pipeline_tag": "text-generation", "tags": ["facebook", "meta", "pytorch", ... | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<d... | null | [
"llama2"
] | null | [
"en"
] | 6,738,415,616 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65e95b4557773f63be2b2bdb | e27eb9d2cfb47179 | da7eeb203d44f9dc | 100,016 | BPE | 99,757 | true | true | true | true | 16 | Sequence | Sequence | ByteLevel | [] | [
"Split",
"Split",
"Split",
"Split",
"Split",
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 394 | deepseek-ai/deepseek-vl-7b-chat | deepseek-ai | null | 9,153 | 427,663 | False | 2024-03-07T06:14:29Z | 2024-03-15T07:04:05Z | transformers | 270 | 0 | null | image-text-to-text | {"parameters": {"F16": 7343990017}, "total": 7343990017} | [
".gitattributes",
"README.md",
"config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"preprocessor_config.json",
"processor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer... | 6f16f00805f45b5249f709ce21820122eeb43556 | [
"transformers",
"safetensors",
"multi_modality",
"image-text-to-text",
"arxiv:2403.05525",
"license:other",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MultiModalityCausalLM"], "model_type": "multi_modality", "tokenizer_config": {"bos_token": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "eos_token": "<\uff5cend\u2581of\u2581sentence\uff5c>", "pad_token": null, "unk_token": null, "use_default_system_prompt": false}} | {
"auto_model": "MultiModalityCausalLM",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "other", "license_name": "deepseek", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null} | ## 1. Introduction
Introducing DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. DeepSeek-VL possesses general multimodal understanding capabilities, capable of processing logical diagrams, web pages, formula recognition, scientific literatur... | null | [
"other",
"deepseek",
"LICENSE"
] | null | null | 7,343,990,017 | null | null | [
"multi_modality",
"MultiModalityCausalLM"
] | [
"image-text-to-text",
null
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
67d1108ba2d6c00266373bb0 | 4f91da2c156973cc | 0a1438da55eb2e11 | 102,400 | BPE | 101,782 | true | true | true | true | 362 | NFKC | Sequence | ByteLevel | [
"NFKC"
] | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 285 | LGAI-EXAONE/EXAONE-Deep-2.4B | LGAI-EXAONE | {
"models": [
{
"_id": "674c45b4810801f2fa142dc3",
"id": "LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct"
}
],
"relation": "finetune"
} | 1,462 | 400,961 | False | 2025-03-12T04:41:47Z | 2026-02-06T06:27:48Z | transformers | 98 | 0 | null | text-generation | {"parameters": {"BF16": 2405327360}, "total": 2405327360} | [
".gitattributes",
"LICENSE",
"README.md",
"assets/EXAONE_Symbol+BI_3d.png",
"assets/exaone_deep_overall_performance.png",
"config.json",
"configuration_exaone.py",
"generation_config.json",
"merges.txt",
"model.safetensors",
"modeling_exaone.py",
"special_tokens_map.json",
"tokenizer.json",
... | 69d80cdf4784e2c182854d83e9b2d02494626a3e | [
"transformers",
"safetensors",
"exaone",
"text-generation",
"lg-ai",
"exaone-deep",
"conversational",
"custom_code",
"en",
"ko",
"arxiv:2503.12524",
"base_model:LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct",
"base_model:finetune:LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct",
"license:other",
"region:us"... | null | {"architectures": ["ExaoneForCausalLM"], "auto_map": {"AutoConfig": "configuration_exaone.ExaoneConfig", "AutoModelForCausalLM": "modeling_exaone.ExaoneForCausalLM", "AutoModelForSequenceClassification": "modeling_exaone.ExaoneForSequenceClassification"}, "model_type": "exaone", "tokenizer_config": {"bos_token": "[BOS]... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_exaone.ExaoneForCausalLM",
"pipeline_tag": "text-generation",
"processor": null
} | {"base_model": "LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct", "datasets": null, "eval_results": null, "language": ["en", "ko"], "library_name": "transformers", "license": "other", "license_name": "exaone", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["lg-ai", "exa... | <p align="center">
<img src="assets/EXAONE_Symbol+BI_3d.png", width="300", style="margin: 40 auto;">
<br>
# EXAONE-Deep-2.4B
## Introduction
We introduce EXAONE Deep, which exhibits superior capabilities in various reasoning tasks including math and coding benchmarks, ranging from 2.4B to 32B parameters developed an... | null | [
"other",
"exaone",
"LICENSE"
] | null | [
"en",
"ko"
] | 2,405,327,360 | null | null | [
"AutoModelForCausalLM",
"exaone",
"modeling_exaone.ExaoneForCausalLM",
"ExaoneForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67b395b39f52a0cf5b112005 | 5913c555399afcb0 | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | true | true | true | 249 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 147 | google/siglip2-base-patch16-384 | google | null | 72,295 | 661,467 | False | 2025-02-17T20:01:55Z | 2025-02-21T04:03:39Z | transformers | 9 | 0 | null | zero-shot-image-classification | {"parameters": {"F32": 375479810}, "total": 375479810} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"preprocessor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | f775b65a79762255128c981547af89addcfe0f88 | [
"transformers",
"safetensors",
"siglip",
"vision",
"zero-shot-image-classification",
"arxiv:2502.14786",
"arxiv:2303.15343",
"arxiv:2209.06794",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"model_type": "siglip", "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Convers... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "zero-shot-image-classification", "tags": ["vision"], "widget": [{"src": "https://huggi... | null | null | [
"apache-2.0"
] | null | null | 375,479,810 | null | null | [
"AutoModel",
"siglip"
] | [
null,
"zero-shot-image-classification"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"logits"
] |
66a01746d370743fd12305b2 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8-dynamic | RedHatAI | {
"models": [
{
"_id": "6698d8a0653e4babe21e1e7d",
"id": "meta-llama/Llama-3.1-8B-Instruct"
}
],
"relation": "quantized"
} | 25,719 | 536,260 | False | 2024-07-23T20:49:10Z | 2026-03-19T19:37:26Z | transformers | 9 | 0 | null | text-generation | {"parameters": {"BF16": 1052315648, "F8_E4M3": 6979321856}, "total": 8031637504} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"recipe.yaml",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | db1dd8e8ab708f96b56b5ed173726519701de484 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"llama-3",
"fp8",
"vllm",
"chat",
"neuralmagic",
"llmcompressor",
"conversational",
"8-bit precision",
"compressed-tensors",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"base_model:meta-l... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "compressed-tensors"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["meta-llama/Llama-3.1-8B-Instruct"], "datasets": null, "eval_results": null, "language": ["en", "de", "fr", "it", "pt", "hi", "es", "th"], "library_name": null, "license": "llama3.1", "license_name": "llama3.1", "license_link": "https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENS... | <h1 style="display: flex; align-items: center; gap: 10px; margin: 0;">
Meta-Llama-3.1-8B-Instruct-FP8-dynamic
<img src="https://www.redhat.com/rhdc/managed-files/Catalog-Validated_model_0.png" alt="Model Icon" width="40" style="margin: 0; padding: 0;" />
</h1>
<a href="https://www.redhat.com/en/products/ai/valid... | null | [
"llama3.1",
"llama3.1",
"https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE"
] | null | [
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th"
] | 8,031,637,504 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
680f35cad0d514746168a1bf | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | unsloth/Qwen3-4B-unsloth-bnb-4bit | unsloth | {
"models": [
{
"_id": "680da769038897aa905586a7",
"id": "Qwen/Qwen3-4B"
}
],
"relation": "quantized"
} | 79,596 | 786,633 | False | 2025-04-28T08:01:14Z | 2025-05-13T20:17:01Z | transformers | 18 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | bbe12ebf9362b3bcbf44e826e4c98910f2c02e72 | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"qwen",
"unsloth",
"conversational",
"en",
"arxiv:2309.00071",
"base_model:Qwen/Qwen3-4B",
"base_model:quantized:Qwen/Qwen3-4B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes"... | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-4B", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-4B/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["qwen3"... | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/qwen3-680edabfb790c8c34a242f95">our collection</a> for all versions of Qwen3 including GGUF, 4-bit & 16-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em>Learn to run Qwen3 correct... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-4B/blob/main/LICENSE"
] | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1794df | af487af51639890d | 101408923f784238 | 64,000 | WordPiece | null | true | true | true | true | 8 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 92 | aubmindlab/bert-large-arabertv02 | aubmindlab | null | 784 | 420,727 | False | 2022-03-02T23:29:05Z | 2023-08-03T12:31:29Z | transformers | 10 | 0 | null | fill-mask | {"parameters": {"I64": 512, "F32": 370541058}, "total": 370541570} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"runs/eval/events.out.tfevents.1608671820.tpu-mother",
"runs/eval/events.out.tfevents.1608673456.tpu-mother",
"runs/eval/events.out.tfevents.1608680655.tpu-mother",
"runs/eval_results.txt"... | 12c9edc789ec5b60444ebb8046de0dde57421fe2 | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"safetensors",
"bert",
"fill-mask",
"ar",
"dataset:wikipedia",
"dataset:Osian",
"dataset:1.5B-Arabic-Corpus",
"dataset:oscar-arabic-unshuffled",
"arxiv:2003.00104",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["wikipedia", "Osian", "1.5B-Arabic-Corpus", "oscar-arabic-unshuffled"], "eval_results": null, "language": "ar", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text"... | # AraBERT v1 & v2 : Pre-training BERT for Arabic Language Understanding
<img src="https://raw.githubusercontent.com/aub-mind/arabert/master/arabert_logo.png" width="100" align="left"/>
**AraBERT** is an Arabic pretrained lanaguage model based on [Google's BERT architechture](https://github.com/google-research/bert). ... | null | null | [
"wikipedia",
"Osian",
"1.5B-Arabic-Corpus",
"oscar-arabic-unshuffled"
] | [
"ar"
] | 370,541,570 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
630bd189a20a5367811e9c5c | c667b81ba860e8b6 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 271 | rajistics/layoutlmv3-finetuned-cord_500 | rajistics | null | 6 | 391,027 | False | 2022-08-28T20:35:21Z | 2022-08-28T21:29:04Z | transformers | 1 | 0 | [{"name": "layoutlmv3-finetuned-cord_500", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "cord-layoutlmv3", "type": "cord-layoutlmv3", "config": "cord", "split": "train", "args": "cord"}, "metrics": [{"name": "Precision", "type": "precision", "value": 0.95092... | token-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"merges.txt",
"preprocessor_config.json",
"pytorch_model.bin",
"runs/Aug28_20-35-15_f2181929f807/1661718927.6585689/events.out.tfevents.1661718927.f2181929f807.2997.1",
"runs/Aug28_20-35-15_f2181929f807/events.out.tfevents.1661718927.f21819... | 8d690de5823ab6a5ab91098f22904e8f9c96564c | [
"transformers",
"pytorch",
"tensorboard",
"layoutlmv3",
"token-classification",
"generated_from_trainer",
"dataset:cord-layoutlmv3",
"license:cc-by-nc-sa-4.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LayoutLMv3ForTokenClassification"], "model_type": "layoutlmv3", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "cls_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normaliz... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoProcessor"
} | {"datasets": ["cord-layoutlmv3"], "license": "cc-by-nc-sa-4.0", "metrics": ["precision", "recall", "f1", "accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "layoutlmv3-finetuned-cord_500", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# layoutlmv3-finetuned-cord_500
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/... | null | [
"cc-by-nc-sa-4.0"
] | [
"cord-layoutlmv3"
] | null | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"LayoutLMv3ForTokenClassification",
"layoutlmv3"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
68922d4a910ecd8aaff1c298 | 441f36ff7235b58e | 985b920c8f6b14f1 | 200,019 | BPE | 446,189 | false | true | true | true | 21 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 54 | trl-internal-testing/tiny-GptOssForCausalLM | trl-internal-testing | null | 345,121 | 1,263,372 | False | 2025-08-05T16:11:54Z | 2025-12-19T19:11:27Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"BF16": 3431024}, "total": 3431024} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 7d144a4b5835d3fbdfe5112a7c22785f8f6f966f | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"trl",
"conversational",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GptOssForCausalLM"], "model_type": "gpt_oss", "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|return|>", "pad_token": "<|endoftext|>"}, "chat_template_jinja": "{#-\n In addition to the normal inputs of `messages` and `tools`, this template also accepts the\n following kwargs:\... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["trl"]} | # Tiny GptOssForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 3,431,024 | null | null | [
"AutoModelForCausalLM",
"GptOssForCausalLM",
"gpt_oss"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65f26e72f52878ab7ae2a1c7 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/Qwen1.5-MoE-A2.7B-Chat | Qwen | null | 32,362 | 542,816 | False | 2024-03-14T03:26:42Z | 2024-04-30T07:45:42Z | transformers | 134 | 1 | null | text-generation | null | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"configuration.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00008.safetensors",
"model-00002-of-00008.safetensors",
"model-00003-of-00008.safetensors",
"model-00004-of-00008.safetensors",
"model-00005-of-00008.safetenso... | ec052fda178e241c7c443468d2fa1db6618996be | [
"transformers",
"safetensors",
"qwen2_moe",
"text-generation",
"chat",
"conversational",
"en",
"license:other",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen2MoeForCausalLM"], "model_type": "qwen2_moe", "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['r... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "other", "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B-Chat/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "ta... | # Qwen1.5-MoE-A2.7B-Chat
## Introduction
Qwen1.5-MoE is a transformer-based MoE decoder-only language model pretrained on a large amount of data.
For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen-moe/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5).
## Model Details
Qwen1.... | null | [
"other",
"tongyi-qianwen",
"https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B-Chat/blob/main/LICENSE"
] | null | [
"en"
] | null | null | null | [
"qwen2_moe",
"AutoModelForCausalLM",
"Qwen2MoeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6614fa47f0f0b8185a0cbdad | e68716652f78d56d | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Strip",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 538 | parler-tts/parler_tts_mini_v0.1 | parler-tts | null | 3,646 | 407,823 | False | 2024-04-09T08:20:23Z | 2024-04-30T18:17:59Z | transformers | 359 | 0 | null | text-to-speech | {"parameters": {"F32": 647027186}, "total": 647027186} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"preprocessor_config.json",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | e02fd18e77d38b49a85c7a9a85189a64b8472544 | [
"transformers",
"safetensors",
"parler_tts",
"text-generation",
"text-to-speech",
"annotation",
"en",
"dataset:parler-tts/mls_eng_10k",
"dataset:blabble-io/libritts_r",
"dataset:parler-tts/libritts_r_tags_tagged_10k_generated",
"dataset:parler-tts/mls-eng-10k-tags_tagged_10k_generated",
"arxiv... | null | {"architectures": ["ParlerTTSForConditionalGeneration"], "model_type": "parler_tts", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": null
} | {"base_model": null, "datasets": ["parler-tts/mls_eng_10k", "blabble-io/libritts_r", "parler-tts/libritts_r_tags_tagged_10k_generated", "parler-tts/mls-eng-10k-tags_tagged_10k_generated"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_l... | <img src="https://huggingface.co/datasets/parler-tts/images/resolve/main/thumbnail.png" alt="Parler Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Parler-TTS Mini v0.1
<a target="_blank" href="https://huggingface.co/spaces/parler-tts/parler_tts_mini">
<img src="https://hugging... | null | [
"apache-2.0"
] | [
"parler-tts/mls_eng_10k",
"blabble-io/libritts_r",
"parler-tts/libritts_r_tags_tagged_10k_generated",
"parler-tts/mls-eng-10k-tags_tagged_10k_generated"
] | [
"en"
] | 647,027,186 | null | null | [
"AutoModelForSeq2SeqLM",
"ParlerTTSForConditionalGeneration",
"parler_tts"
] | [
"text-to-speech",
"text-generation"
] | [
"text",
"audio"
] | [
"text"
] | [
"text",
"audio"
] |
621ffdc036468d709f17514f | c017a029b62d722b | 94eb381d2d7a0200 | 593 | BPE | 0 | false | true | true | true | 7 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 128 | DeepChem/ChemBERTa-10M-MLM | DeepChem | null | 1,246 | 401,397 | False | 2022-03-02T23:29:04Z | 2022-01-20T18:01:08Z | transformers | 5 | 0 | null | fill-mask | null | [
".gitattributes",
"added_tokens.json",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | a5cfe173103cff3149e7322130342a4880010cba | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "model_type": "roberta", "tokenizer_config": {"unk_token": {"content": "[UNK]", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normaliz... | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"roberta",
"AutoModelForMaskedLM",
"RobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.