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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6341a99c9948f573f372a01b | 7a4cc4a6090329ff | ab8f40e5a89244c4 | 250,680 | BPE | 250,434 | false | true | true | true | 4 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 31 | bigscience/bloomz-3b | bigscience | null | 11,816 | 767,436 | False | 2022-10-08T16:47:24Z | 2023-05-27T17:26:10Z | transformers | 81 | 0 | [{"name": "bloomz-3b1", "results": [{"task": {"type": "Coreference resolution"}, "dataset": {"type": "winogrande", "name": "Winogrande XL (xl)", "config": "xl", "split": "validation", "revision": "a80f460359d1e9a67c006011c94de42a8759430c"}, "metrics": [{"type": "Accuracy", "value": 53.67, "verified": false}]}, {"task":... | text-generation | {"parameters": {"F16": 3002557440}, "total": 3002557440} | [
".gitattributes",
"README.md",
"config.json",
"logs/logs/xp3capmixnewcodelonglossseq/main_log.txt",
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"logs/tensorboard/xp3capmixnewcodelonglossseq/events.out.tfevents.1664821892.r9i7n5.1076818.0",
"logs/tensor... | 31eefcb2bcd69632925adf07e090debafe95436d | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"bloom",
"text-generation",
"ak",
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"ne",
"nso",
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"or",
"pa",
... | null | {"architectures": ["BloomForCausalLM"], "model_type": "bloom", "tokenizer_config": {"unk_token": "<unk>", "eos_token": "</s>", "bos_token": "<s>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["bigscience/xP3"], "language": ["ak", "ar", "as", "bm", "bn", "ca", "code", "en", "es", "eu", "fon", "fr", "gu", "hi", "id", "ig", "ki", "kn", "lg", "ln", "ml", "mr", "ne", "nso", "ny", "or", "pa", "pt", "rn", "rw", "sn", "st", "sw", "ta", "te", "tn", "ts", "tum", "tw", "ur", "vi", "wo", "xh", "yo", "zh",... | 
# 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 | [
"bigscience-bloom-rail-1.0"
] | [
"bigscience/xP3"
] | [
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
"rw",
"sn",
"st",
"sw",
"ta",
"te",
"tn",
"ts",
"tum",
"tw",
... | 3,002,557,440 | null | null | [
"AutoModelForCausalLM",
"BloomForCausalLM",
"bloom"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67535af98b36d55caa6b1e4b | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | unsloth/Llama-3.3-70B-Instruct-bnb-4bit | unsloth | {
"models": [
{
"_id": "6745f28f9333dfcc06268b1e",
"id": "meta-llama/Llama-3.3-70B-Instruct"
}
],
"relation": "quantized"
} | 9,414 | 808,774 | False | 2024-12-06T20:13:45Z | 2025-11-25T06:03:57Z | transformers | 52 | 0 | null | text-generation | {"parameters": {"F32": 4330240, "BF16": 2102665216, "U8": 70590329742}, "total": 70553706496} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model-00001-of-00008.safetensors",
"model-00002-of-00008.safetensors",
"model-00003-of-00008.safetensors",
"model-00004-of-00008.safetensors",
"model-00005-of-00008.safetensors",
"model-00006-of-00008... | 644fb67263c036423f7bdfa771cc43b3389eab45 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-3",
"meta",
"facebook",
"unsloth",
"pytorch",
"conversational",
"en",
"arxiv:2204.05149",
"base_model:meta-llama/Llama-3.3-70B-Instruct",
"base_model:quantized:meta-llama/Llama-3.3-70B-Instruct",
"license:llama3.3",
"tex... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|eot_id|>", "pad_token": "<|finetune_right_pad_id|>", "unk_token": null, "chat_templa... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Llama-3.3-70B-Instruct", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "llama3.3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["llama-3", "llama", "meta", "facebook", "... | ## ***See [our collection](https://huggingface.co/collections/unsloth/llama-33-all-versions-67535d7d994794b9d7cf5e9f) for all versions of Llama 3.3 including GGUF, 4-bit and original 16-bit formats.***
# Finetune Llama 3.3, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tes... | null | [
"llama3.3"
] | null | [
"en"
] | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1802a1 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | sentence-transformers/bert-base-nli-stsb-mean-tokens | sentence-transformers | null | 4,303 | 757,345 | False | 2022-03-02T23:29:05Z | 2025-03-06T13:34:45Z | sentence-transformers | 2 | 0 | null | sentence-similarity | {"parameters": {"I64": 512, "F32": 109482240}, "total": 109482752} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"added_tokens.json",
"config.json",
"config_sentence_transformers.json",
"flax_model.msgpack",
"model.safetensors",
"modules.json",
"onnx/model.onnx",
"onnx/model_O1.onnx",
"onnx/model_O2.onnx",
"onnx/model_O3.onnx",
"onnx/model_O4.on... | c1e99553cc170c78b16717e93e8042552f5bef20 | [
"sentence-transformers",
"pytorch",
"tf",
"jax",
"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-base-nli-stsb-mean-tokens
This is a [sentence... | null | [
"apache-2.0"
] | null | null | 109,482,752 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
686fabae2fb74b6dbfe2dc8b | 52f24e37c2a463b7 | e228821354aa0ea9 | 64,400 | BPE | 63,683 | false | true | true | true | 507 | null | Sequence | Sequence | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 404 | LiquidAI/LFM2-1.2B | LiquidAI | null | 84,065 | 2,463,124 | False | 2025-07-10T12:01:50Z | 2026-02-12T17:32:59Z | transformers | 350 | 0 | null | text-generation | {"parameters": {"BF16": 1170340608}, "total": 1170340608} | [
".gitattributes",
"LICENSE",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 933cee00d754fb3bfe06c644c0cb95453f2d8bb2 | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"liquid",
"edge",
"conversational",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"arxiv:2511.23404",
"license:other",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Lfm2ForCausalLM"], "model_type": "lfm2", "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|im_end|>", "pad_token": "<|pad|>", "use_default_system_prompt": false}, "chat_template_jinja": "{{- bos_token -}}\n{%- set system_prompt = \"\" -%}\n{%- set ns = namespace(system_prompt=\"\"... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "ar", "zh", "fr", "de", "ja", "ko", "es"], "library_name": "transformers", "license": "other", "license_name": "lfm1.0", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["liquid", "... | <center>
<div style="text-align: center;">
<img
src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/7_6D7rWrLxp2hb6OHSV1p.png"
alt="Liquid AI"
style="width: 100%; max-width: 66%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
/>
</div>
<d... | null | [
"other",
"lfm1.0",
"LICENSE"
] | null | [
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es"
] | 1,170,340,608 | null | null | [
"Lfm2ForCausalLM",
"AutoModelForCausalLM",
"lfm2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65705c94f6b924b7690af252 | 0f39f02b65fe5cfd | 539cc58b8fdaf772 | 51,864 | BPE | 50,000 | false | true | true | true | 1,608 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 405 | distil-whisper/distil-small.en | distil-whisper | null | 73,144 | 862,160 | False | 2023-12-06T11:35:48Z | 2024-03-25T12:09:13Z | transformers | 112 | 0 | null | automatic-speech-recognition | {"parameters": {"F16": 166132224}, "total": 166132224} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"ggml-distil-small.en.bin",
"ggml-distil-small.en.fp32.bin",
"merges.txt",
"model.fp32.safetensors",
"model.safetensors",
"normalizer.json",
"onnx/decoder_model.onnx",
"onnx/decoder_model_merged.onnx... | 5ced4c93e41c640e72b423d596cc7dc0de3f8419 | [
"transformers",
"pytorch",
"tensorboard",
"onnx",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"transformers.js",
"en",
"arxiv:2311.00430",
"arxiv:2210.13352",
"license:mit",
"region:us"
] | null | {"architectures": ["WhisperForConditionalGeneration"], "model_type": "whisper", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForSpeechSeq2Seq",
"custom_class": null,
"pipeline_tag": "automatic-speech-recognition",
"processor": "AutoProcessor"
} | {"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": "automatic-speech-recognition", "tags": ["audio", "automatic-speech-recognition", "transform... | # Distil-Whisper: distil-small.en
Distil-Whisper was proposed in the paper [Robust Knowledge Distillation via Large-Scale Pseudo Labelling](https://arxiv.org/abs/2311.00430).
It is a distilled version of the Whisper model that is **6 times faster**, 49% smaller, and performs **within 1% WER**
on out-of-distribution e... | null | [
"mit"
] | null | [
"en"
] | 166,132,224 | null | null | [
"WhisperForConditionalGeneration",
"whisper",
"AutoModelForSpeechSeq2Seq"
] | [
"automatic-speech-recognition"
] | [
"multimodal"
] | [
"audio"
] | [
"text"
] |
676a8942ad042e047d99ff10 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/QVQ-72B-Preview | Qwen | {
"models": [
{
"_id": "67502205096baaa441081069",
"id": "Qwen/Qwen2-VL-72B"
}
],
"relation": "finetune"
} | 216 | 739,450 | False | 2024-12-24T10:13:22Z | 2025-01-12T01:54:38Z | transformers | 609 | 0 | null | image-text-to-text | {"parameters": {"BF16": 73405560320}, "total": 73405560320} | [
".gitattributes",
"LICENSE",
"README.md",
"chat_template.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00038.safetensors",
"model-00002-of-00038.safetensors",
"model-00003-of-00038.safetensors",
"model-00004-of-00038.safetensors",
"model-00005-of-00038.safetenso... | 24425f65e80be6804b75ae0a3dc1e5570e660a25 | [
"transformers",
"safetensors",
"qwen2_vl",
"image-text-to-text",
"chat",
"conversational",
"en",
"arxiv:2409.12191",
"base_model:Qwen/Qwen2-VL-72B",
"base_model:finetune:Qwen/Qwen2-VL-72B",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
... | null | {"architectures": ["Qwen2VLForConditionalGeneration"], "model_type": "qwen2_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 helpfu... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": "Qwen/Qwen2-VL-72B", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "other", "license_name": "qwen", "license_link": "https://huggingface.co/Qwen/QVQ-72B-Preview/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "image-text-to... | # QVQ-72B-Preview
<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
**QVQ-72B-Preview** is an experimental research m... | null | [
"other",
"qwen",
"https://huggingface.co/Qwen/QVQ-72B-Preview/blob/main/LICENSE"
] | null | [
"en"
] | 73,405,560,320 | null | null | [
"AutoModelForImageTextToText",
"qwen2_vl",
"Qwen2VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
669fee5ee7ab2772921debd3 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | unsloth/Meta-Llama-3.1-405B-bnb-4bit | unsloth | null | 66 | 736,861 | False | 2024-07-23T17:54:38Z | 2024-09-11T08:25:27Z | transformers | 16 | 0 | null | text-generation | {"parameters": {"BF16": 4206837760, "F32": 24754464, "U8": 414198313134}, "total": 418429905358} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00044.safetensors",
"model-00002-of-00044.safetensors",
"model-00003-of-00044.safetensors",
"model-00004-of-00044.safetensors",
"model-00005-of-00044.safetensors",
"model-00006-of-00044.safetensors",
"model-0... | b77489abd4cb571c2ad05aa1a05f6bedb193e227 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-3",
"meta",
"facebook",
"unsloth",
"en",
"license:llama3.1",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|end_of_text|>", "pad_token": "<|finetune_right_pad_id|>"}} | {
"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": "llama3.1", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["llama-3", "llama", "meta", "facebook", "unsloth", "transformers"]} | # Finetune Llama 3.1, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here: https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/D... | null | [
"llama3.1"
] | null | [
"en"
] | 418,429,905,358 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
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"text"
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"Metaspace"
] | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 35 | unsloth/mistral-7b-bnb-4bit | unsloth | null | 28,996 | 1,125,542 | False | 2023-12-25T17:15:38Z | 2024-09-11T02:09:37Z | transformers | 30 | 0 | null | text-generation | {"parameters": {"F32": 486912, "BF16": 262410240, "U8": 7197503300}, "total": 7460400452} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer.model.v1",
"tokenizer_config.json"
] | 3c47be0aa392c058e26ede776ecd2d5416fa5d28 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"unsloth",
"mistral-7b",
"bnb",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<unk>", "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": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "transformers", "mistral", "mistral-7b", "bnb"]} | # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
Directly quantized 4bit model with `bitsandbytes`.
We have a Google Colab Tesla T4 notebook for Mistral 7b here: https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing
[<img src="https://raw.githubuserconten... | null | [
"apache-2.0"
] | null | [
"en"
] | 7,460,400,452 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Replace"
] | [
"Split"
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"Replace",
"ByteFallback",
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] | 406 | google/gemma-3n-E4B-it | google | {
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{
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"id": "google/gemma-3n-E4B"
}
],
"relation": "finetune"
} | 50,880 | 1,223,625 | manual | 2025-06-03T18:17:07Z | 2025-07-14T13:56:17Z | transformers | 889 | 2 | null | image-text-to-text | null | [
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"image-text-to-text",
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"audio-text-to-text",
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"arxiv:1905.07830",
"arxiv:1905.10044",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1705.03551",
... | null | {"architectures": ["Gemma3nForConditionalGeneration"], "model_type": "gemma3n", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}, "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n {%- i... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": "google/gemma-3n-E4B", "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": ["automatic-speech-recognition", "automatic-s... | null | null | [
"gemma"
] | null | null | null | null | null | [
"AutoModelForImageTextToText",
"gemma3n",
"Gemma3nForConditionalGeneration"
] | [
"image-text-to-text",
"video-text-to-text",
"automatic-speech-recognition"
] | [
"vision",
"multimodal"
] | [
"text",
"audio",
"image"
] | [
"text"
] |
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"ByteLevel"
] | [
"ByteLevel"
] | 112 | togethercomputer/GPT-JT-6B-v1 | togethercomputer | null | 889 | 756,417 | False | 2022-11-24T06:09:34Z | 2023-01-24T06:08:17Z | transformers | 302 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"merges.txt",
"pytorch_model.bin",
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"tokenizer_config.json",
"vocab.json"
] | f34aa35f906895602c1f86f5685e598afdea8051 | [
"transformers",
"pytorch",
"gptj",
"text-generation",
"en",
"dataset:natural_instructions",
"dataset:the_pile",
"dataset:cot",
"dataset:Muennighoff/P3",
"arxiv:2205.05131",
"arxiv:2210.11399",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTJForCausalLM"], "model_type": "gptj", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized"... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["natural_instructions", "the_pile", "cot", "Muennighoff/P3"], "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": "text-generation", "tags": null, "infe... | <h1 style="font-size: 42px">GPT-JT<h1/>
***<p style="font-size: 24px">Feel free to try out our [Online Demo](https://huggingface.co/spaces/togethercomputer/GPT-JT)!</p>***
# Model Summary
> With a new decentralized training algorithm, we fine-tuned GPT-J (6B) on 3.53 billion tokens, resulting in GPT-JT (6B), a mod... | null | [
"apache-2.0"
] | [
"natural_instructions",
"the_pile",
"cot",
"Muennighoff/P3"
] | [
"en"
] | null | null | null | [
"gptj",
"AutoModelForCausalLM",
"GPTJForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 407 | mistral-experimental/pixtral-12b | mistral-experimental | null | 224,395 | 1,434,205 | False | 2024-09-13T19:32:26Z | 2025-01-27T11:53:06Z | transformers | 103 | 0 | null | image-text-to-text | {"parameters": {"BF16": 12682739712}, "total": 12682739712} | [
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"transformers",
"safetensors",
"llava",
"image-text-to-text",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlavaForConditionalGeneration"], "model_type": "llava", "processor_config": {"chat_template": "{%- if messages[0][\"role\"] == \"system\" %}{%- set system_message = messages[0][\"content\"] %}{%- set loop_messages = messages[1:] %}\n{%- else %}{%- set loop_messages = messages %}{%- endif %}{{- bos_t... | {
"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": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null} | null | null | [
"apache-2.0"
] | null | null | 12,682,739,712 | null | null | [
"AutoModelForImageTextToText",
"LlavaForConditionalGeneration",
"llava"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
65cee0266da01df536288bef | e25ebce15fc2f56b | 3085d01101e6b8e8 | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 408 | r1char9/rubert-base-cased-russian-sentiment | r1char9 | null | 23,644 | 847,989 | False | 2024-02-16T04:10:14Z | 2025-04-23T06:08:14Z | transformers | 13 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 364be199aed60beda23010f04ba76d47d45b404a | [
"transformers",
"pytorch",
"bert",
"text-classification",
"sentiment-analysis",
"multi-class-classification",
"sentiment analysis",
"rubert",
"sentiment",
"russian",
"multiclass",
"classification",
"ru",
"license:mit",
"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": null, "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-analysis", "multi-class... | Модель [RuBERT](https://huggingface.co/DeepPavlov/rubert-base-cased) была дообучена на задачу __sentiment classification__ для короткого __Russian__ корпуса.
Задача представляет собой __multi-class classification__ со следующими метками:
```yaml
0: neutral
1: positive
2: negative
```
## Usage
```python
from transfor... | null | [
"mit"
] | null | [
"ru"
] | null | null | [
"f1",
"roc_auc",
"precision",
"recall"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
672e6b62ca6d5a4563f663fb | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | OrcaDB/cde-small-v1 | OrcaDB | null | 4,774 | 751,214 | False | 2024-11-08T19:49:54Z | 2025-01-02T19:34:35Z | sentence-transformers | 4 | 0 | [{"name": "cde-small-v1", "results": [{"dataset": {"config": "en", "name": "MTEB AmazonCounterfactualClassification (en)", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205", "split": "test", "type": "mteb/amazon_counterfactual"}, "metrics": [{"type": "accuracy", "value": 87.02985074626866, "verified": false}, {"ty... | feature-extraction | {"parameters": {"F32": 281140992}, "total": 281140992} | [
".gitattributes",
"README.md",
"config.json",
"config_sentence_transformers.json",
"misc.py",
"model.safetensors",
"modules.json",
"sentence_bert_config.json",
"sentence_transformers_impl.py",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 5f600a5f2c1b599782bac7478eab6483704bee20 | [
"sentence-transformers",
"safetensors",
"feature-extraction",
"mteb",
"transformers",
"custom_code",
"arxiv:2410.02525",
"model-index",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DatasetTransformer"], "auto_map": {"AutoConfig": "jxm/cde-small-v1--misc.ContextualModelConfig", "AutoModel": "jxm/cde-small-v1--model.DatasetTransformer"}, "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": "jxm/cde-small-v1--model.DatasetTransformer",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"tags": ["mteb", "transformers", "sentence-transformers"], "model-index": [{"name": "cde-small-v1", "results": [{"task": {"type": "Classification"}, "dataset": {"name": "MTEB AmazonCounterfactualClassification (en)", "type": "mteb/amazon_counterfactual", "config": "en", "split": "test", "revision": "e8379541af4e31359c... | # Contextual Document Embeddings (CDE)
**Link to code: github.com/jxmorris12/cde**
Our new model that naturally integrates "context tokens" into the embedding process. As of October 1st, 2024, `cde-small-v1` is the best small model (under 400M params) on the [MTEB leaderboard](https://huggingface.co/spaces/mteb/leade... | null | null | null | null | 281,140,992 | null | null | [
"AutoModel",
"jxm/cde-small-v1--model.DatasetTransformer",
"DatasetTransformer"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
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"Split",
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"ByteLevel"
] | 142 | mlx-community/Meta-Llama-3.1-70B-Instruct-4bit | mlx-community | null | 13,020 | 809,867 | False | 2024-07-23T14:40:04Z | 2024-11-26T19:48:34Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"F16": 2206081024, "U32": 8819048448}, "total": 11025129472} | [
".gitattributes",
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... | 7772c93cf077b642f5503dd8d763a4176d7d406c | [
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"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"mlx",
"conversational",
"en",
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"fr",
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"pt",
"hi",
"es",
"th",
"license:llama3.1",
"text-generation-inference",
"endpoints_compatible",
"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": 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... | # mlx-community/Meta-Llama-3.1-70B-Instruct-4bit
The Model [mlx-community/Meta-Llama-3.1-70B-Instruct-4bit](https://huggingface.co/mlx-community/Meta-Llama-3.1-70B-Instruct-4bit) was converted to MLX format from [meta-llama/Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct) usi... | null | [
"llama3.1"
] | null | [
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th"
] | 11,025,129,472 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"ByteLevel"
] | [
"ByteLevel"
] | 376 | ibm-granite/granite-3.3-8b-instruct | ibm-granite | {
"models": [
{
"_id": "67f65cdd156c9664279df2e8",
"id": "ibm-granite/granite-3.3-8b-base"
}
],
"relation": "finetune"
} | 74,898 | 1,142,894 | False | 2025-04-09T11:41:39Z | 2025-05-12T06:39:42Z | transformers | 154 | 0 | null | text-generation | {"parameters": {"BF16": 8170864640}, "total": 8170864640} | [
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"base_model:ibm-granite/granite-3.3-8b-base",
"base_model:finetune:ibm-granite/granite-3.3-8b-base",
"license:apache-2.0",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GraniteForCausalLM"], "model_type": "granite", "tokenizer_config": {"bos_token": "<|end_of_text|>", "chat_template": "{# Alias tools -> available_tools #}\n{%- if tools and not available_tools -%}\n {%- set available_tools = tools -%}\n{%- endif -%}\n{%- if messages[0]['role'] == 'system' %}\n ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["ibm-granite/granite-3.3-8b-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-generation", "tags": ["language", "granite-3.3"], ... | null | null | [
"apache-2.0"
] | null | null | 8,170,864,640 | null | null | [
"granite",
"AutoModelForCausalLM",
"GraniteForCausalLM"
] | [
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] | [
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] | [
"text"
] | [
"text"
] |
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"Split",
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] | [
"ByteLevel"
] | 31 | bigscience/bloom-3b | bigscience | null | 9,019 | 795,537 | False | 2022-05-19T11:52:27Z | 2023-04-14T08:43:29Z | transformers | 94 | 0 | [{"name": "bloom", "results": [{"task": {"type": "text-generation", "name": "text generation"}, "dataset": {"name": "arc_challenge", "type": "arc_challenge"}, "metrics": [{"name": "acc", "type": "acc", "value": 0.27986348122866894, "verified": false}]}, {"task": {"type": "text-generation", "name": "text generation"}, "... | text-generation | {"parameters": {"F16": 3002557440}, "total": 3002557440} | [
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] | 52bc5b43010b4844513826b8be3f78c7344c37d7 | [
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"safetensors",
"bloom",
"text-generation",
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
... | null | {"architectures": ["BloomForCausalLM"], "model_type": "bloom", "tokenizer_config": {"unk_token": "<unk>", "eos_token": "</s>", "bos_token": "<s>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"language": ["ak", "ar", "as", "bm", "bn", "ca", "code", "en", "es", "eu", "fon", "fr", "gu", "hi", "id", "ig", "ki", "kn", "lg", "ln", "ml", "mr", "ne", "nso", "ny", "or", "pa", "pt", "rn", "rw", "sn", "st", "sw", "ta", "te", "tn", "ts", "tum", "tw", "ur", "vi", "wo", "xh", "yo", "zh", "zhs", "zht", "zu"], "license":... | <h1 style='text-align: center '>BLOOM LM</h1>
<h2 style='text-align: center '><em>BigScience Large Open-science Open-access Multilingual Language Model</em> </h2>
<h3 style='text-align: center '>Model Card</h3>
<img src="https://s3.amazonaws.com/moonup/production/uploads/1657124309515-5f17f0a0925b9863e28ad517.png" al... | null | [
"bigscience-bloom-rail-1.0"
] | null | [
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
"rw",
"sn",
"st",
"sw",
"ta",
"te",
"tn",
"ts",
"tum",
"tw",
... | 3,002,557,440 | null | null | [
"AutoModelForCausalLM",
"BloomForCausalLM",
"bloom"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
678f31161881e899e8fc8bf4 | 36935258f89e8e9e | 83d37c6e8ee56b77 | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 315 | mlx-community/DeepSeek-R1-Distill-Qwen-32B-4bit | mlx-community | {
"models": [
{
"_id": "678e15048143a819dd01a3c1",
"id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
}
],
"relation": "quantized"
} | 3,347 | 740,746 | False | 2025-01-21T05:31:02Z | 2025-02-26T17:40:53Z | transformers | 46 | 0 | null | text-generation | {"parameters": {"F16": 1024955392, "U32": 4095344640}, "total": 5120300032} | [
".gitattributes",
"README.md",
"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.json",
"tokenizer.json",
"tokenizer_config.json"
] | 4e0d3848a0ad8f9fb54638891e4928f04fcca978 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"mlx",
"conversational",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"region:us"
] | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4}, "tokenizer_config": {"bos_token": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_firs... | {
"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": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["mlx"]} | # mlx-community/DeepSeek-R1-Distill-Qwen-32B-4bit
The Model [mlx-community/DeepSeek-R1-Distill-Qwen-32B-4bit](https://huggingface.co/mlx-community/DeepSeek-R1-Distill-Qwen-32B-4bit) was
converted to MLX format from [deepseek-ai/DeepSeek-R1-Distill-Qwen-32B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-3... | null | null | null | null | 5,120,300,032 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68780ff44a0209cc20da5d23 | b3310d158ab6e0dc | 66be3297e0980489 | 28,895 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 409 | OpenMed/OpenMed-NER-DiseaseDetect-BioMed-335M | OpenMed | null | 202,469 | 2,114,797 | False | 2025-07-16T20:47:48Z | 2025-08-05T09:41:31Z | transformers | 7 | 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"
] | a62e2a2da5ff7d6b79024ba906f481581466ea61 | [
"transformers",
"safetensors",
"bert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"disease-entity-recognition",
"medical-diagnosis",
"pathology",
"biocuration",
"disease",
"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"
] |
67feba1d76f7fc788ad9c508 | 46323c0f61df476d | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 49 | mlx-community/gemma-3-27b-it-qat-4bit | mlx-community | {
"models": [
{
"_id": "67ff92c1a93c489f94ab29c6",
"id": "OpenGVLab/InternVL3-1B-Instruct"
}
],
"relation": "finetune"
} | 114,648 | 1,175,994 | False | 2025-04-15T19:57:17Z | 2025-04-19T15:27:04Z | transformers | 22 | 1 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.json",
"config.json",
"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",
"pr... | fc4e000f32af1b7b6779294e490a7d2a80bac611 | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"internvl",
"custom_code",
"mlx",
"conversational",
"multilingual",
"dataset:OpenGVLab/MMPR-v1.2",
"base_model:OpenGVLab/InternVL3-1B-Instruct",
"base_model:finetune:OpenGVLab/InternVL3-1B-Instruct",
"license:other",
"text-gene... | null | {"architectures": ["Gemma3ForConditionalGeneration"], "model_type": "gemma3", "processor_config": {"chat_template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n {%- if messages[0]['content'] is string -%}\n {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n {%- else -%}\n ... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["OpenGVLab/InternVL3-1B-Instruct"], "datasets": ["OpenGVLab/MMPR-v1.2"], "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "other", "license_name": "qwen", "license_link": "https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE", "metrics": null, ... | # mlx-community/gemma-3-27b-it-qat-4bit
This model was converted to MLX format from [`google/gemma-3-27b-it-qat-q4_0-unquantized`]() using mlx-vlm version **0.1.23**.
Refer to the [original model card](https://huggingface.co/google/gemma-3-27b-it-qat-q4_0-unquantized) for more details on the model.
## Use with mlx
```... | null | [
"other",
"qwen",
"https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE"
] | [
"OpenGVLab/MMPR-v1.2"
] | [
"multilingual"
] | null | null | null | [
"AutoModelForImageTextToText",
"Gemma3ForConditionalGeneration",
"gemma3"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
621ffdc136468d709f17a848 | 06f29accdd3d2e59 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 410 | doc2query/msmarco-t5-base-v1 | doc2query | null | 294 | 728,155 | False | 2022-03-02T23:29:05Z | 2022-01-10T10:22:10Z | transformers | 6 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json",
"train_script.py",
"training_args.bin"
] | e673dca0dff1f19fda73ac62420eedf0219e692b | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:sentence-transformers/embedding-training-data",
"arxiv:1904.08375",
"arxiv:2104.08663",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"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"
} | {"base_model": null, "datasets": ["sentence-transformers/embedding-training-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": null, "widget": [{"text": "Python is a... | # doc2query/msmarco-t5-base-v1
This is a [doc2query](https://arxiv.org/abs/1904.08375) model based on T5 (also known as [docT5query](https://cs.uwaterloo.ca/~jimmylin/publications/Nogueira_Lin_2019_docTTTTTquery-v2.pdf)).
It can be used for:
- **Document expansion**: You generate for your paragraphs 20-40 querie... | null | [
"apache-2.0"
] | [
"sentence-transformers/embedding-training-data"
] | [
"en"
] | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc136468d709f17a216 | 820723d44f714bed | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 73 | cross-encoder/nli-MiniLM2-L6-H768 | cross-encoder | {
"models": [
{
"_id": "621ffdc136468d709f17e8fa",
"id": "nreimers/MiniLMv2-L6-H768-distilled-from-RoBERTa-Large"
}
],
"relation": "quantized"
} | 59,433 | 843,228 | False | 2022-03-02T23:29:05Z | 2025-04-15T08:00:19Z | sentence-transformers | 13 | 0 | null | zero-shot-classification | {"parameters": {"I64": 514, "F32": 82120707}, "total": 82121221} | [
".gitattributes",
"CESoftmaxAccuracyEvaluator_AllNLI-dev_results.csv",
"README.md",
"config.json",
"merges.txt",
"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_av... | b95119ce93d3e065de6214e38cd4a97b0f2f2c6d | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"openvino",
"roberta",
"text-classification",
"transformers",
"zero-shot-classification",
"en",
"dataset:nyu-mll/multi_nli",
"dataset:stanfordnlp/snli",
"base_model:nreimers/MiniLMv2-L6-H768-distilled-from-RoBERTa-Large",
"base_mod... | 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": ["nreimers/MiniLMv2-L6-H768-distilled-from-RoBERTa-Large"], "datasets": ["nyu-mll/multi_nli", "stanfordnlp/snli"], "eval_results": null, "language": "en", "library_name": "sentence-transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": n... | null | null | [
"apache-2.0"
] | [
"nyu-mll/multi_nli",
"stanfordnlp/snli"
] | [
"en"
] | 82,121,221 | null | [
"accuracy"
] | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"zero-shot-classification",
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64ca02286a26cddbecdc9132 | 382b5a4eb98f0296 | d965e4a9140ecf72 | 21,128 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 33 | BAAI/bge-large-zh | BAAI | null | 13,085 | 853,457 | False | 2023-08-02T07:13:44Z | 2023-10-12T03:38:28Z | transformers | 345 | 1 | null | feature-extraction | {"parameters": {"I64": 512, "F32": 325522432}, "total": 325522944} | [
".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"
] | b5d9f5c027e87b6f0b6fa4b614f8f9cdc45ce0e8 | [
"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-large-zh-v1.5](https://huggingface.co/BAAI/bge-large-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=#frequ... | null | [
"mit"
] | null | [
"zh"
] | 325,522,944 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
66ec161712bd743cfe94a0f4 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-Math-7B-Instruct | Qwen | {
"models": [
{
"_id": "66e81d43f85e59f0618f3b24",
"id": "Qwen/Qwen2.5-Math-7B"
}
],
"relation": "finetune"
} | 83,962 | 1,460,048 | False | 2024-09-19T12:16:23Z | 2024-09-23T06:10:43Z | transformers | 89 | 0 | null | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"tokenizer.json",
"... | ef9926d75ab1d54532f6a30dd5e760355eb9aa4d | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2409.12122",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region... | 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 {{- 'Please reason step by step, an... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-Math-7B", "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-Math-7B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag":... | # Qwen2.5-Math-7B-Instruct
> [!Warning]
> <div align="center">
> <b>
> 🚨 Qwen2.5-Math mainly supports solving English and Chinese math problems through CoT and TIR. We do not recommend using this series of models for other tasks.
> </b>
> </div>
## Introduction
In August 2024, we released the first series of mathem... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct/blob/main/LICENSE"
] | null | [
"en"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68f8dfe68cb208be9702aa87 | 2fed9702c2b0b4da | f776c55d8128e158 | 200,054 | BPE | 199,744 | true | true | false | true | 54 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 411 | MiniMaxAI/MiniMax-M2 | MiniMaxAI | null | 116,505 | 1,869,243 | False | 2025-10-22T13:45:10Z | 2025-12-23T08:37:43Z | transformers | 1,488 | 2 | null | text-generation | {"parameters": {"F32": 62654720, "BF16": 1230021632, "F8_E4M3": 227410968576}, "total": 228703644928} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"configuration_minimax_m2.py",
"docs/mlx_deploy_guide.md",
"docs/sglang_deploy_guide.md",
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"... | 757303d492a50514c312788b5247a4f696a4c6a3 | [
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67d132f0a6fc6460be7587d8 | 46323c0f61df476d | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
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<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/gemma-3-67d12b7e8816ec6efa7e4e5b">our collection</a> for all versions of Gemma 3 including GGUF, 4-bit & 16-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em><a href="https://docs.... | null | [
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"... | e9a141a2091ea561b96483212645a2a05e6f99fc | [
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We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here: https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing
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# ##############################################################################################
#
# This model has been uploaded to HuggingFace by https://huggingface.co/drAbreu
# The model is based on the NVIDIA checkpoint located at
# https://catalog.ngc.nvidia.com/orgs/nvidia/models/biomegatron345muncased
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X-CLIP model (large-sized, patch resolution of 14) trained fully-supervised on [Kinetics-400](https://www.deepmind.com/open-source/kinetics). It was introduced in the paper [Expanding Language-Image Pretrained Models for General Video Recognition](https://arxiv.org/abs/2208.02816) by Ni e... | null | [
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XGLM-564M is a multilingual autoregressive language model (with 564 million parameters) trained on a balanced corpus of a diverse set of 30 languages totaling 500 billion sub-tokens. It was introduced in the paper [Few-shot Learning with Multilingual Language Models](https://arxiv.org/abs/2112.10668) by Xi... | null | [
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] | 414 | microsoft/xclip-base-patch16-zero-shot | microsoft | null | 2,794 | 742,092 | False | 2022-09-07T17:52:51Z | 2023-09-12T12:13:40Z | transformers | 27 | 0 | [{"name": "nielsr/xclip-base-patch16-zero-shot", "results": [{"task": {"type": "video-classification"}, "dataset": {"name": "HMDB-51", "type": "hmdb-51"}, "metrics": [{"type": "top-1 accuracy", "value": 44.6, "verified": false}]}, {"task": {"type": "video-classification"}, "dataset": {"name": "UCF101", "type": "ucf101"... | video-classification | {"parameters": {"I64": 274, "F32": 194941440}, "total": 194941714} | [
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"vision",
"video-classification",
"en",
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] | null | {"architectures": ["XCLIPModel"], "model_type": "xclip", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<|startoftext|>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized": ... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoProcessor"
} | {"language": "en", "license": "mit", "tags": ["vision", "video-classification"], "model-index": [{"name": "nielsr/xclip-base-patch16-zero-shot", "results": [{"task": {"type": "video-classification"}, "dataset": {"name": "HMDB-51", "type": "hmdb-51"}, "metrics": [{"type": "top-1 accuracy", "value": 44.6, "verified": fal... | # X-CLIP (base-sized model)
X-CLIP model (base-sized, patch resolution of 16) trained on [Kinetics-400](https://www.deepmind.com/open-source/kinetics). It was introduced in the paper [Expanding Language-Image Pretrained Models for General Video Recognition](https://arxiv.org/abs/2208.02816) by Ni et al. and first rel... | null | [
"mit"
] | null | [
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] | 194,941,714 | null | null | [
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"feature-extraction"
] | [
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"multimodal"
] | [
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"video"
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"embeddings"
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687a0d97dd4fba78804bd748 | 5b8a6156b5b6e013 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 37 | OpenMed/OpenMed-NER-AnatomyDetect-ElectraMed-109M | OpenMed | null | 198,773 | 2,069,711 | False | 2025-07-18T09:02:15Z | 2025-08-05T09:45:39Z | transformers | 1 | 0 | null | token-classification | {"parameters": {"BF16": 108893955}, "total": 108893955} | [
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"special_tokens_map.json",
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"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 207f22237c9b992750b45fbc4003066c50c4fbe1 | [
"transformers",
"safetensors",
"bert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"anatomical-entity-recognition",
"medical-terminology",
"anatomy",
"healthcare",
"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... | # 🧬 [OpenMed-NER-AnatomyDetect-ElectraMed-109M](https://huggingface.co/OpenMed/OpenMed-NER-AnatomyDetect-ElectraMed-109M)
**Specialized model for Anatomical Entity Recognition - Anatomical structures and body parts**
[](https://opensource.org/lice... | null | [
"apache-2.0"
] | null | [
"en"
] | 108,893,955 | null | null | [
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"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
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] | d3017ef2c2c1395888c8d635c5e0508bcb0ac78d | [
"transformers",
"safetensors",
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"image-text-to-text",
"got",
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"ocr2.0",
"multilingual",
"arxiv:2409.01704",
"arxiv:2405.14295",
"arxiv:2312.06109",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GotOcr2ForConditionalGeneration"], "model_type": "got_ocr2", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["multilingual"], "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": ["got", "vision-language", "ocr2.0"]} | <h1>General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model - HF Transformers 🤗 implementation
</h1>
[🤗 Spaces Demo](https://huggingface.co/spaces/yonigozlan/GOT-OCR-Transformers) | [🌟GitHub](https://github.com/Ucas-HaoranWei/GOT-OCR2.0/) | [📜Paper](https://arxiv.org/abs/2409.01704)</a>
[Haoran Wei*]... | null | [
"apache-2.0"
] | null | [
"multilingual"
] | 560,528,640 | null | null | [
"GotOcr2ForConditionalGeneration",
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"got_ocr2"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | DiscoResearch/mixtral-7b-8expert | DiscoResearch | null | 42 | 715,201 | False | 2023-12-08T23:33:07Z | 2023-12-11T08:58:28Z | transformers | 264 | 0 | null | text-generation | null | [
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"pytorch_model-00002-of-00019.bin"... | 2d0aefa97f3104cfb6368f231fd8287b4e95f7ff | [
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"it",
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] | null | {"architectures": ["MixtralForCausalLM"], "auto_map": {"AutoConfig": "DiscoResearch/mixtral-7b-8expert--configuration_moe_mistral.MixtralConfig", "AutoModelForCausalLM": "DiscoResearch/mixtral-7b-8expert--modeling_moe_mistral.MixtralForCausalLM"}, "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_t... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "fr", "it", "es", "de"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Mixtral 7b 8 Expert
This is a preliminary HuggingFace implementation of the newly released MoE model by MistralAi. Make sure to load with `trust_remote_code=True`.
Thanks to @dzhulgakov for his e... | null | [
"apache-2.0"
] | null | [
"en",
"fr",
"it",
"es",
"de"
] | null | null | null | [
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] | 234 | lmms-lab/llava-onevision-qwen2-0.5b-ov | lmms-lab | null | 13,906 | 800,311 | False | 2024-07-28T14:24:01Z | 2024-09-02T07:24:13Z | transformers | 26 | 0 | [{"name": "llava-onevision-qwen-0.5b-ov", "results": [{"task": {"type": "multimodal"}, "dataset": {"name": "AI2D", "type": "ai2d"}, "metrics": [{"type": "accuracy", "value": 57.1, "name": "accuracy", "verified": false}]}, {"task": {"type": "multimodal"}, "dataset": {"name": "ChartQA", "type": "chartqa"}, "metrics": [{"... | text-generation | {"parameters": {"BF16": 893618208}, "total": 893618208} | [
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"zh",
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"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlavaQwenForCausalLM"], "model_type": "llava", "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['role... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"datasets": ["lmms-lab/LLaVA-OneVision-Data"], "language": ["en", "zh"], "library_name": "transformers", "license": "apache-2.0", "metrics": ["accuracy"], "tags": ["multimodal"], "model-index": [{"name": "llava-onevision-qwen-0.5b-ov", "results": [{"task": {"type": "multimodal"}, "dataset": {"name": "AI2D", "type": "a... | # LLaVA-OneVision
Play with the model on the [LLaVA OneVision Chat](https://llava-onevision.lmms-lab.com/).
## Table of Contents
1. [Model Summary](##model-summary)
2. [Use](##use)
3. [Limitations](##limitations)
4. [Training](##training)
5. [Licens... | null | [
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] | null | {"architectures": ["SiglipModel"], "model_type": "siglip", "tokenizer_config": {"eos_token": "</s>", "pad_token": "</s>", "unk_token": "<unk>"}} | {
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SigLIP model pre-trained on WebLi at resolution 256x256. It was introduced in the paper [Sigmoid Loss for Language Image Pre-Training](https://arxiv.org/abs/2303.15343) by Zhai et al. and first released in [this repository](https://github.com/google-research/big_vision).
Disclaimer: The ... | null | [
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] | null | null | 652,150,786 | null | null | [
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] | 237 | OpenMed/OpenMed-NER-DNADetect-SuperClinical-184M | OpenMed | null | 52 | 1,747,446 | False | 2025-07-18T08:54:56Z | 2025-08-05T09:45:00Z | transformers | 1 | 0 | null | token-classification | {"parameters": {"BF16": 183840011}, "total": 183840011} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"model.safetensors",
"openmed_vs_sota_grouped_bars.png",
"special_tokens_map.json",
"spm.model",
"test_results.json",
"tokenizer.json",
"tokenizer_config.json"
] | 78583647233f6aad6764c770950b4ffa352541fa | [
"transformers",
"safetensors",
"deberta-v2",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"protein-recognition",
"gene-recognition",
"molecular-biology",
"genomics",
"dna",
"rna",
"cell_line",
"cell_type",
"protein",
"en",
"arxiv:2508.01630",
"license:apach... | null | {"architectures": ["DebertaV2ForTokenClassification"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "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"
] | 183,840,011 | null | null | [
"DebertaV2ForTokenClassification",
"AutoModelForTokenClassification",
"deberta-v2"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
62555b5b93dead146187b37f | 35f8a93a304f6b78 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 6 | s-nlp/Mutual_Implication_Score | s-nlp | null | 4,246 | 719,295 | False | 2022-04-12T10:58:35Z | 2025-03-24T11:21:14Z | transformers | 6 | 0 | null | null | {"parameters": {"I64": 514, "F32": 355361793}, "total": 355362307} | [
".gitattributes",
"MIS.jpg",
"README.md",
"config.json",
"corr_main.jpg",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 532ad7079bdbf7352948cc463f525cf57f026cc8 | [
"transformers",
"pytorch",
"safetensors",
"roberta",
"paraphrase detection",
"paraphrase",
"paraphrasing",
"en",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification_all_in_one_local"], "model_type": "roberta", "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": fal... | {
"auto_model": "RobertaForSequenceClassification_all_in_one_local",
"custom_class": null,
"pipeline_tag": null,
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["paraphrase detection", "paraphrase", "paraphrasing"], "licenses": ["cc-by-nc-sa"]} | ## Model overview
Mutual Implication Score is a symmetric measure of text semantic similarity
based on a RoBERTA model pretrained for natural language inference
and fine-tuned on a paraphrase detection dataset.
The code for inference and evaluation of the model is available [here](https://github.com/skoltech-nlp/mut... | null | [
"cc-by-nc-sa"
] | null | [
"en"
] | 355,362,307 | null | null | [
"roberta",
"RobertaForSequenceClassification_all_in_one_local"
] | [
null
] | null | null | null |
63a600e6c1a26c19c80cec05 | 2d0341bd3a73bae6 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 32 | philschmid/flan-t5-base-samsum | philschmid | null | 846 | 713,781 | False | 2022-12-23T19:26:30Z | 2022-12-23T19:32:18Z | transformers | 93 | 0 | [{"name": "flan-t5-base-samsum", "results": [{"task": {"name": "Sequence-to-sequence Language Modeling", "type": "text2text-generation"}, "dataset": {"name": "samsum", "type": "samsum", "config": "samsum", "split": "train", "args": "samsum"}, "metrics": [{"name": "Rouge1", "type": "rouge", "value": 47.2358, "verified":... | null | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"logs/1671812016.0361354/events.out.tfevents.1671812016.ip-172-31-95-43.46092.1",
"logs/events.out.tfevents.1671812016.ip-172-31-95-43.46092.0",
"logs/events.out.tfevents.1671823577.ip-172-31-95-43.46092.2",
"pytorch_model.bin",
"special_to... | dab5b3234360d786065ab29c6dd5af00a0bff05f | [
"transformers",
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:samsum",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["samsum"], "license": "apache-2.0", "metrics": ["rouge"], "tags": ["generated_from_trainer"], "model-index": [{"name": "flan-t5-base-samsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "samsum", "type": "samsum", "config": "... | <!-- 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. -->
# flan-t5-base-samsum
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on th... | null | [
"apache-2.0"
] | [
"samsum"
] | null | null | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
674492372d8f7ac9804f54bb | 54895f2d8faef315 | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | true | true | true | 249 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 50 | trl-internal-testing/tiny-Gemma2ForCausalLM | trl-internal-testing | null | 131,776 | 1,099,757 | False | 2024-11-25T15:05:27Z | 2025-12-19T19:09:47Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 2098760}, "total": 2098760} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 499ba6cf37232e9d88b89348d850879d43367f02 | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Gemma2ForCausalLM"], "model_type": "gemma2", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}, "chat_template_jinja": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System rol... | {
"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 Gemma2ForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 2,098,760 | null | null | [
"AutoModelForCausalLM",
"gemma2",
"Gemma2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65cca50c633d8fe1b3cb9b97 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | BioMistral/BioMistral-7B | BioMistral | null | 143,994 | 1,095,354 | False | 2024-02-14T11:33:32Z | 2024-02-21T20:53:27Z | transformers | 494 | 0 | null | text-generation | null | [
".gitattributes",
"Image+Title.png",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"runs/events.out.tfevents.1703180761.jean-zay-iam23.1019751.0",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json",
"wordart_blue_m_rectangle.png... | 9a11e1ffa817c211cbb52ee1fb312dc6b61b40a5 | [
"transformers",
"pytorch",
"tensorboard",
"mistral",
"text-generation",
"medical",
"biology",
"conversational",
"fr",
"en",
"de",
"nl",
"es",
"pt",
"pl",
"ro",
"it",
"arxiv:2402.10373",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...'... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["fr", "en", "de", "nl", "es", "pt", "pl", "ro", "it"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["medical", "biology... | <p align="center">
<img src="https://huggingface.co/BioMistral/BioMistral-7B/resolve/main/wordart_blue_m_rectangle.png?download=true" alt="drawing" width="250"/>
</p>
# BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains
**Abstract:**
Large Language Models (LLMs) have demon... | null | [
"apache-2.0"
] | null | [
"fr",
"en",
"de",
"nl",
"es",
"pt",
"pl",
"ro",
"it"
] | null | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63ead0cee35a4dfbb8e4f6a4 | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | EleutherAI/pythia-1b-deduped | EleutherAI | null | 10,746 | 758,491 | False | 2023-02-14T00:07:42Z | 2023-07-10T15:04:31Z | transformers | 19 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 7199d8fc61a6d565cd1f3c62bf11525b563e13b2 | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"pythia",
"en",
"dataset:EleutherAI/the_pile_deduplicated",
"arxiv:2304.01373",
"arxiv:2101.00027",
"arxiv:2201.07311",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"depl... | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["EleutherAI/the_pile_deduplicated"], "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": ["pytorch", "causal-lm", "pythia"]} | The *Pythia Scaling Suite* is a collection of models developed to facilitate
interpretability research [(see paper)](https://arxiv.org/pdf/2304.01373.pdf).
It contains two sets of eight models of sizes
70M, 160M, 410M, 1B, 1.4B, 2.8B, 6.9B, and 12B. For each size, there are two
models: one trained on the Pile, and ... | null | [
"apache-2.0"
] | [
"EleutherAI/the_pile_deduplicated"
] | [
"en"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6744926347d61b15da9f7aa4 | f5e7f943c396c76b | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 52 | trl-internal-testing/tiny-Phi3ForCausalLM | trl-internal-testing | null | 114,039 | 1,039,974 | False | 2024-11-25T15:06:11Z | 2025-12-19T19:10:53Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 514136}, "total": 514136} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 7213681d74f9b264bcbc9e88a14de38517612119 | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Phi3ForCausalLM"], "model_type": "phi3", "tokenizer_config": {"bos_token": "<s>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "unk_token": "<unk>", "use_default_system_prompt": false}, "chat_template_jinja": "{% for message in messages %}{% if message['role'] == 'system' and message[... | {
"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 Phi3ForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 514,136 | null | null | [
"AutoModelForCausalLM",
"phi3",
"Phi3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
655379e56cfe0c04a979d0a3 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | protectai/xlm-roberta-base-language-detection-onnx | protectai | {
"models": [
{
"_id": "621ffdc136468d709f17ebd6",
"id": "papluca/xlm-roberta-base-language-detection"
}
],
"relation": "quantized"
} | 6,207 | 727,132 | False | 2023-11-14T13:45:09Z | 2024-03-25T12:05:26Z | transformers | 6 | 0 | [{"name": "xlm-roberta-base-language-detection", "results": []}] | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"model.onnx",
"model_optimized.onnx",
"model_quantized.onnx",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | dce2fa14a0dc61b6f889537e9ad4fccf083b22bd | [
"transformers",
"onnx",
"xlm-roberta",
"text-classification",
"language",
"language-detection",
"multilingual",
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"hi",
"it",
"ja",
"nl",
"pl",
"pt",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh",
"arxiv:1911.02116",
"base_mo... | 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"
} | {"base_model": "papluca/xlm-roberta-base-language-detection", "datasets": null, "eval_results": [], "language": ["multilingual", "ar", "bg", "de", "el", "en", "es", "fr", "hi", "it", "ja", "nl", "pl", "pt", "ru", "sw", "th", "tr", "ur", "vi", "zh"], "library_name": null, "license": "mit", "license_name": null, "license... | # ONNX version of papluca/xlm-roberta-base-language-detection
**This model is a conversion of [papluca/xlm-roberta-base-language-detection](https://huggingface.co/papluca/xlm-roberta-base-language-detection) to ONNX** format using the [🤗 Optimum](https://huggingface.co/docs/optimum/index) library.
## Model descripti... | null | [
"mit"
] | null | [
"multilingual",
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"hi",
"it",
"ja",
"nl",
"pl",
"pt",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh"
] | null | null | [
"accuracy",
"f1"
] | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64896b01f4d5239fac77883e | 2ad52fdc0a02add9 | 079f8303f7d4d91e | 32,101 | Unigram | null | true | true | true | true | 104 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 417 | sjrhuschlee/flan-t5-large-squad2 | sjrhuschlee | {
"models": [
{
"_id": "63526f4c7e4cc3135fd0ff1a",
"id": "google/flan-t5-large"
}
],
"relation": "adapter"
} | 29 | 707,896 | False | 2023-06-14T07:23:45Z | 2023-09-28T12:43:10Z | transformers | 5 | 0 | [{"name": "sjrhuschlee/flan-t5-large-squad2", "results": [{"task": {"type": "question-answering", "name": "Question Answering"}, "dataset": {"name": "squad_v2", "type": "squad_v2", "config": "squad_v2", "split": "validation"}, "metrics": [{"type": "exact_match", "value": 86.819, "name": "Exact Match", "verified": false... | question-answering | {"parameters": {"F32": 750253058}, "total": 750253058} | [
".gitattributes",
"README.md",
"adapter_config.json",
"adapter_model.bin",
"added_tokens.json",
"config.json",
"model.safetensors",
"modeling_t5qa.py",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | a8eb9abb87449914e7ecbaed6efc28fdda7c64cf | [
"transformers",
"pytorch",
"safetensors",
"t5",
"question-answering",
"squad",
"squad_v2",
"lora",
"peft",
"custom_code",
"en",
"dataset:squad_v2",
"dataset:squad",
"base_model:google/flan-t5-large",
"base_model:adapter:google/flan-t5-large",
"license:mit",
"model-index",
"text-gen... | null | {"architectures": ["T5ForQuestionAnswering"], "auto_map": {"AutoModelForQuestionAnswering": "modeling_t5qa.T5ForQuestionAnswering"}, "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": "google/flan-t5-large", "datasets": ["squad_v2", "squad"], "language": ["en"], "library_name": "transformers", "license": "mit", "tags": ["question-answering", "squad", "squad_v2", "t5", "lora", "peft"], "model-index": [{"name": "sjrhuschlee/flan-t5-large-squad2", "results": [{"task": {"type": "question-... | # flan-t5-large for Extractive QA
This is the [flan-t5-large](https://huggingface.co/google/flan-t5-large) model, fine-tuned using the [SQuAD2.0](https://huggingface.co/datasets/squad_v2) dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Extractive Question Answerin... | null | [
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"text"
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"text"
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"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 418 | OpenMed/OpenMed-NER-OrganismDetect-BioPatient-108M | OpenMed | null | 185,970 | 2,005,145 | False | 2025-07-16T20:04:18Z | 2025-08-05T09:38:13Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 107721987}, "total": 107721987} | [
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687807873f4cfbeb9a29de1b | 6a67cbd79bab1e59 | cf1efbe71ef28fc9 | 50,368 | BPE | 50,009 | true | true | true | true | 116 | NFC | ByteLevel | ByteLevel | [
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"gene/protein",
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621ffdc136468d709f1814a6 | 0202b54b045bdf64 | a00df6594a092a68 | 66,119 | BPE | 63,978 | false | true | true | true | 1 | null | WhitespaceSplit | BPEDecoder | null | [
"WhitespaceSplit"
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"BPEDecoder"
] | 99 | vinai/phobert-large | vinai | null | 4,312 | 731,942 | False | 2022-03-02T23:29:05Z | 2024-08-20T03:48:24Z | transformers | 12 | 0 | null | fill-mask | null | [
".gitattributes",
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] | 1c7880f20db59c0054c6de5afd71b012369f6ee4 | [
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"roberta",
"fill-mask",
"vi",
"arxiv:2003.00744",
"license:mit",
"endpoints_compatible",
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] | null | {"architectures": ["RobertaForMaskedLM"], "model_type": "roberta"} | {
"auto_model": "AutoModelForMaskedLM",
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"pipeline_tag": "fill-mask",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["vi"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # <a name="introduction"></a> PhoBERT: Pre-trained language models for Vietnamese
Pre-trained PhoBERT models are the state-of-the-art language models for Vietnamese ([Pho](https://en.wikipedia.org/wiki/Pho), i.e. "Phở", is a popular food in Vietnam):
- Two PhoBERT versions of "base" and "large" are the first publ... | null | [
"mit"
] | null | [
"vi"
] | null | null | null | [
"roberta",
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67449252360728c707008a48 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | trl-internal-testing/tiny-LlamaForCausalLM-3.1 | trl-internal-testing | null | 105,398 | 1,009,300 | False | 2024-11-25T15:05:54Z | 2025-12-19T19:10:27Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 2054056}, "total": 2054056} | [
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"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | d159f90ff59bde5fb9ce7034ad5782a926de29c0 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|eot_id|>"}, "chat_template_jinja": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"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 LlamaForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 2,054,056 | null | null | [
"AutoModelForCausalLM",
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"LlamaForCausalLM"
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] | [
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] |
65a6418e0a0bcd589653d9b4 | 89a5128d694e9242 | 081b543d8f95004e | 32,002 | BPE | 58,980 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
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] | 419 | TheBloke/Nous-Hermes-2-Mixtral-8x7B-DPO-GPTQ | TheBloke | {
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"relation": "quantized"
} | 14 | 704,390 | False | 2024-01-16T08:42:54Z | 2024-01-16T11:05:43Z | transformers | 26 | 0 | [{"name": "Nous-Hermes-2-Mixtral-8x7B-DPO", "results": []}] | text-generation | {"parameters": {"I32": 46439333888, "BF16": 263475200, "F16": 8716288}, "total": 46711525376} | [
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] | 3bad824e55ebf468b1313560eca97504fa8d0e89 | [
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"base_model:quantized:NousResearch/Nous... | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if a... | {
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} | {"base_model": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", "datasets": null, "eval_results": [], "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "Nous-Hermes-2-Mixtral-8x7B-DPO", "pipeline_tag": null, "tags": ["Mixtral", "i... | <!-- markdownlint-disable MD041 -->
<!-- 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:... | null | [
"apache-2.0"
] | null | [
"en"
] | 46,711,525,376 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
669447b5fc25100d1ebbfbab | bafc5e0c20be7cd8 | 82d3db801e5d7f68 | 49,152 | BPE | 48,900 | false | true | false | true | 17 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 115 | HuggingFaceTB/SmolLM-360M | HuggingFaceTB | null | 29,150 | 839,364 | False | 2024-07-14T21:48:37Z | 2024-08-01T20:12:58Z | transformers | 70 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
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"merges.txt",
"model.safetensors",
"onnx/model.onnx",
"onnx/model_bnb4.onnx",
"onnx/model_fp16.onnx",
"onnx/model_int8.onnx",
"onnx/model_q4.onnx",
"onnx/model_quantized.onnx",
"onnx/model_uint8.onnx",
"special_tokens_... | 59f7ef243ee09a72cbc14cb054393a3e3b771d41 | [
"transformers",
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"dataset:HuggingFaceTB/smollm-corpus",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["HuggingFaceTB/smollm-corpus"], "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": null, "tags": null} | # SmolLM
<center>
<img src="https://huggingface.co/datasets/HuggingFaceTB/images/resolve/main/banner_smol.png" alt="SmolLM" width="1100" height="600">
</center>
## Table of Contents
1. [Model Summary](##model-summary)
2. [Limitations](##limitations)
3. [Training](##training)
4. [License](##license)
5. [Citation... | null | [
"apache-2.0"
] | [
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] | [
"en"
] | null | null | null | [
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] | [
"text"
] | [
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"ByteLevel"
] | [
"ByteLevel"
] | 186 | trl-internal-testing/tiny-OPTForCausalLM | trl-internal-testing | null | 15,091 | 801,964 | False | 2024-11-25T15:06:08Z | 2025-12-19T19:10:45Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"F16": 523640}, "total": 523640} | [
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] | 2f8f69129aba9fa6692e5f0696bffb5ccd09f837 | [
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"safetensors",
"opt",
"text-generation",
"trl",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["OPTForCausalLM"], "model_type": "opt", "tokenizer_config": {"bos_token": "</s>", "eos_token": "</s>", "pad_token": "<pad>", "unk_token": "</s>"}} | {
"auto_model": "AutoModelForCausalLM",
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} | {"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 OPTForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 523,640 | null | null | [
"OPTForCausalLM",
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] | [
"text-generation"
] | [
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] | [
"text"
] | [
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] |
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"Metaspace"
] | [
"Replace",
"ByteFallback",
"Fuse",
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] | 8932eb9b599cc4061ee9207ca74b1505aaa1852c | [
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"mistral",
"text-generation",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"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}, "chat_template_jinja": "{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['cont... | {
"auto_model": "AutoModelForCausalLM",
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} | {"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 MistralForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 513,960 | null | null | [
"AutoModelForCausalLM",
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"MistralForCausalLM"
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] | [
"text"
] | [
"text"
] | [
"text"
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{
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"id": "answerdotai/ModernBERT-base"
}
],
"relation": "finetune"
} | 214,330 | 1,122,037 | False | 2025-01-20T03:03:48Z | 2025-07-04T10:03:26Z | transformers | 194 | 2 | null | sentence-similarity | {"parameters": {"F16": 149014272}, "total": 149014272} | [
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"onnx/model_q4f16.onnx",
"onnx/m... | e7f32e3c00f91d699e8c43b53106206bcc72bb22 | [
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"sentence-similarity",
"en",
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"base_model:fin... | null | {"architectures": ["ModernBertModel"], "model_type": "modernbert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
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} | {"base_model": ["answerdotai/ModernBERT-base"], "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": "sentence-similarity", "tags": ["sentence-transformers", "... | null | null | [
"apache-2.0"
] | null | [
"en"
] | 149,014,272 | null | null | [
"AutoModel",
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"Replace",
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] | 106 | trl-internal-testing/tiny-GemmaForCausalLM | trl-internal-testing | null | 108,267 | 1,010,778 | False | 2024-11-25T15:05:32Z | 2025-12-19T19:09:54Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 2098728}, "total": 2098728} | [
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"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | ca81dfc4db4cc333c2bb4ef003e7b4f0bb1deaa8 | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}, "chat_template_jinja": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role ... | {
"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 GemmaForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 2,098,728 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6744924e54cca9a938c265f0 | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | trl-internal-testing/tiny-LlamaForCausalLM-3 | trl-internal-testing | null | 104,405 | 1,003,713 | False | 2024-11-25T15:05:50Z | 2025-12-19T19:10:20Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 2054056}, "total": 2054056} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | af8d47e69da5b5fcdf8f4605b5c2feefb6e20348 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|eot_id|>"}, "chat_template_jinja": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'... | {
"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 LlamaForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 2,054,056 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6641487429be04778b9180f0 | 31dabac8dc7ce889 | 7d900c9c71170270 | 257,153 | BPE | 580,604 | true | true | true | true | 218 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 138 | google/paligemma-3b-pt-224 | google | null | 81,889 | 887,103 | manual | 2024-05-12T22:53:40Z | 2024-09-21T10:14:25Z | transformers | 426 | 5 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"preprocessor_config.json",
"special_tokens_map.json",
"token... | 35e4f46485b4d07967e7e9935bc3786aad50687c | [
"transformers",
"safetensors",
"paligemma",
"image-text-to-text",
"arxiv:2310.09199",
"arxiv:2303.15343",
"arxiv:2403.08295",
"arxiv:1706.03762",
"arxiv:2010.11929",
"arxiv:2209.06794",
"arxiv:2209.04372",
"arxiv:2103.01913",
"arxiv:2205.12522",
"arxiv:2110.11624",
"arxiv:2108.03353",
... | null | {"architectures": ["PaliGemmaForConditionalGeneration"], "model_type": "paligemma", "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 PaliGemma on Hugging Face... | null | null | [
"gemma"
] | null | null | null | null | null | [
"PaliGemmaForConditionalGeneration",
"AutoModelForImageTextToText",
"paligemma"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
645d80ef4e2cf468917eef13 | d239c54d1f5946a3 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 420 | grammarly/coedit-large | grammarly | null | 112,977 | 933,369 | False | 2023-05-11T23:57:35Z | 2024-04-28T02:30:16Z | transformers | 154 | 0 | null | null | {"parameters": {"F32": 783092736}, "total": 783092736} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json",
"training_args.bin"
] | 5637bcdf9d8d4419f97c8cfea36f7d35c79232b6 | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"en",
"dataset:facebook/asset",
"dataset:wi_locness",
"dataset:GEM/wiki_auto_asset_turk",
"dataset:discofuse",
"dataset:zaemyung/IteraTeR_plus",
"dataset:jfleg",
"dataset:grammarly/coedit",
"arxiv:2305.09857",
"licen... | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["facebook/asset", "wi_locness", "GEM/wiki_auto_asset_turk", "discofuse", "zaemyung/IteraTeR_plus", "jfleg", "grammarly/coedit"], "eval_results": null, "language": ["en"], "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": ["sari", "b... | # Model Card for CoEdIT-Large
This model was obtained by fine-tuning the corresponding `google/flan-t5-large` model on the CoEdIT dataset. Details of the dataset can be found in our paper and repository.
**Paper:** CoEdIT: Text Editing by Task-Specific Instruction Tuning
**Authors:** Vipul Raheja, Dhruv Kumar, Ryan ... | null | [
"cc-by-nc-4.0"
] | [
"facebook/asset",
"wi_locness",
"GEM/wiki_auto_asset_turk",
"discofuse",
"zaemyung/IteraTeR_plus",
"jfleg",
"grammarly/coedit"
] | [
"en"
] | 783,092,736 | null | [
"sari",
"bleu",
"accuracy"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
62d6b7751c1bf309b847354a | 4155560ecd9aee89 | 9f0f55e4bc9b7218 | 57,544 | Unigram | null | true | true | true | true | 27 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 421 | naver-clova-ix/donut-base-finetuned-rvlcdip | naver-clova-ix | null | 2,889 | 706,154 | False | 2022-07-19T13:53:57Z | 2024-03-09T13:02:19Z | transformers | 20 | 0 | null | image-to-text | null | [
".gitattributes",
".gitignore",
"README.md",
"added_tokens.json",
"config.json",
"preprocessor_config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 7b37b465a4a1aaa9b7775e1a46d131a5794e266b | [
"transformers",
"pytorch",
"vision-encoder-decoder",
"image-text-to-text",
"donut",
"image-to-text",
"vision",
"arxiv:2111.15664",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["VisionEncoderDecoderModel"], "model_type": "vision-encoder-decoder", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": {"__type": "AddedToken", "content": "<mask>", "lstrip": true, "normalized": true, "rstrip": false, "single_word": false}, "pad_token": ... | {
"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": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["donut", "image-to-text", "vision"]} | # Donut (base-sized model, fine-tuned on RVL-CDIP)
Donut model fine-tuned on RVL-CDIP. It was introduced in the paper [OCR-free Document Understanding Transformer](https://arxiv.org/abs/2111.15664) by Geewok et al. and first released in [this repository](https://github.com/clovaai/donut).
Disclaimer: The team releas... | null | [
"mit"
] | null | null | null | null | null | [
"AutoModelForImageTextToText",
"vision-encoder-decoder",
"VisionEncoderDecoderModel"
] | [
"image-text-to-text",
"image-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
6647c622775f85537328e28d | bfe694f64f4a18f5 | daab2a732bab72e2 | 128,001 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Strip",
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 22 | nvidia/domain-classifier | nvidia | null | 13,446 | 749,519 | False | 2024-05-17T21:03:30Z | 2025-09-22T20:43:34Z | transformers | 96 | 0 | null | null | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"model.pth",
"model.safetensors",
"special_tokens_map.json",
"spm.model",
"tokenizer.json",
"tokenizer_config.json"
] | b18c7bfe703a82f4689cc3e6c79481e7f42343cb | [
"transformers",
"safetensors",
"deberta-v2",
"pytorch_model_hub_mixin",
"model_hub_mixin",
"arxiv:2111.09543",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"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": ["pytorch_model_hub_mixin", "model_hub_mixin"]} | # NemoCurator Domain Classifier
# Model Overview
This is a text classification model to classify documents into one of 26 domain classes:
```
'Adult', 'Arts_and_Entertainment', 'Autos_and_Vehicles', 'Beauty_and_Fitness', 'Books_and_Literature', 'Business_and_Industrial', 'Computers_and_Electronics', 'Finance', 'Food_a... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModel",
"deberta-v2"
] | [
null
] | null | null | null |
632dce875f0b9fbb3df5f9ec | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | neulab/codebert-javascript | neulab | null | 54 | 698,836 | False | 2022-09-23T15:19:35Z | 2023-02-27T20:56:02Z | transformers | 15 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | b4883b1904319236d05b11519dcf96d532faac0d | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"arxiv:2302.05527",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "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, "rstri... | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | This is a `microsoft/codebert-base-mlm` model, trained for 1,000,000 steps (with `batch_size=32`) on **JavaScript** code from the `codeparrot/github-code-clean` dataset, on the masked-language-modeling task.
It is intended to be used in CodeBERTScore: [https://github.com/neulab/code-bert-score](https://github.com/neu... | null | null | null | null | null | null | null | [
"roberta",
"AutoModelForMaskedLM",
"RobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f17b452 | 2012b52fa41ec860 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 113 | geralt/MechDistilGPT2 | geralt | null | 23 | 691,567 | False | 2022-03-02T23:29:05Z | 2023-09-11T15:49:22Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | dfff309247bbb79abbb8ab6daf966d634c039969 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"Causal Language modeling",
"CLM",
"arxiv:2105.09680",
"arxiv:1910.09700",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_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": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["Causal Language modeling", "text-generation", "CLM"], "model_index": [{"name": "MechDisti... | # MechDistilGPT2
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Environmental Impact](#environmental-impact)
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
## Model Details
- ... | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63a14f4c45edac9f750cf607 | 9749c35928f4a7de | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 129 | hkunlp/instructor-base | hkunlp | null | 11,717 | 773,821 | False | 2022-12-20T05:59:40Z | 2023-01-21T06:31:16Z | sentence-transformers | 119 | 0 | [{"name": "final_base_results", "results": [{"task": {"type": "Classification"}, "dataset": {"type": "mteb/amazon_counterfactual", "name": "MTEB AmazonCounterfactualClassification (en)", "config": "en", "split": "test", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205"}, "metrics": [{"type": "accuracy", "value": 8... | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"2_Dense/config.json",
"2_Dense/pytorch_model.bin",
"README.md",
"config.json",
"config_sentence_transformers.json",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"to... | 0b2f22542d2bd6d60dbff22d22f12c15e6562736 | [
"sentence-transformers",
"pytorch",
"t5",
"text-embedding",
"embeddings",
"information-retrieval",
"beir",
"text-classification",
"language-model",
"text-clustering",
"text-semantic-similarity",
"text-evaluation",
"prompt-retrieval",
"text-reranking",
"feature-extraction",
"sentence-si... | null | {"architectures": ["T5EncoderModel"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": "AutoTokenizer"
} | {"language": "en", "license": "apache-2.0", "pipeline_tag": "sentence-similarity", "tags": ["text-embedding", "embeddings", "information-retrieval", "beir", "text-classification", "language-model", "text-clustering", "text-semantic-similarity", "text-evaluation", "prompt-retrieval", "text-reranking", "sentence-transfor... | # hkunlp/instructor-base
We introduce **Instructor**👨🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e.g., classification, retrieval, clustering, text evaluation, etc.) and domains (e.g., science, finance, etc.) ***by simply providing the task instruction, wit... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"t5",
"T5EncoderModel",
"AutoModel"
] | [
null,
"sentence-similarity",
"feature-extraction",
"text-classification"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
65d4e8bbd80effa0b8deaedb | ac35e3244a1fc1f8 | 5ff1c70e91becad4 | 49,152 | BPE | 48,872 | false | true | false | true | 38 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 121 | bigcode/starcoder2-7b | bigcode | null | 19,118 | 775,793 | False | 2024-02-20T18:00:27Z | 2024-06-11T08:15:50Z | transformers | 210 | 0 | [{"name": "starcoder2-7b", "results": [{"task": {"type": "text-generation"}, "dataset": {"name": "CruxEval-I", "type": "cruxeval-i"}, "metrics": [{"type": "pass@1", "value": 34.6, "verified": false}]}, {"task": {"type": "text-generation"}, "dataset": {"name": "DS-1000", "type": "ds-1000"}, "metrics": [{"type": "pass@1"... | text-generation | {"parameters": {"BF16": 7173923840}, "total": 7173923840} | [
".gitattributes",
"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",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"... | bb9afde76d7945da5745592525db122d4d729eb1 | [
"transformers",
"safetensors",
"starcoder2",
"text-generation",
"code",
"dataset:bigcode/the-stack-v2-train",
"arxiv:2305.13245",
"arxiv:2205.14135",
"arxiv:2004.05150",
"arxiv:2207.14255",
"arxiv:2402.19173",
"license:bigcode-openrail-m",
"model-index",
"text-generation-inference",
"end... | null | {"architectures": ["Starcoder2ForCausalLM"], "model_type": "starcoder2", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["bigcode/the-stack-v2-train"], "library_name": "transformers", "license": "bigcode-openrail-m", "pipeline_tag": "text-generation", "tags": ["code"], "inference": {"parameters": {"temperature": 0.2, "top_p": 0.95}}, "widget": [{"text": "def print_hello_world():", "example_title": "Hello world", "group": "P... | # StarCoder2
<center>
<img src="https://huggingface.co/datasets/bigcode/admin_private/resolve/main/starcoder2_banner.png" alt="SC2" width="900" height="600">
</center>
## Table of Contents
1. [Model Summary](##model-summary)
2. [Use](##use)
3. [Limitations](##limitations)
4. [Training](##training)
5. [License](... | null | [
"bigcode-openrail-m"
] | [
"bigcode/the-stack-v2-train"
] | null | 7,173,923,840 | null | null | [
"AutoModelForCausalLM",
"starcoder2",
"Starcoder2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65f761468fb2b15357a2a334 | 987859235b346536 | e979b3df4a15d906 | 32,001 | BPE | 61,249 | false | true | true | true | 4 | null | Metaspace | Sequence | null | [
"Metaspace"
] | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 385 | llava-hf/llava-v1.6-vicuna-13b-hf | llava-hf | null | 3,067 | 784,437 | False | 2024-03-17T21:31:50Z | 2025-01-27T11:25:31Z | transformers | 22 | 0 | null | image-text-to-text | {"parameters": {"F16": 13351499776}, "total": 13351499776} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.json",
"config.json",
"generation_config.json",
"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",
... | 745cfbdb14dfeff9bcc6eb731937102e88ea3024 | [
"transformers",
"safetensors",
"llava_next",
"image-text-to-text",
"vision",
"conversational",
"en",
"arxiv:2310.03744",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlavaNextForConditionalGeneration"], "model_type": "llava_next", "processor_config": {"chat_template": "{% for message in messages %}{% if message['role'] != 'system' %}{{ message['role'].upper() + ': '}}{% endif %}{# Render all images first #}{% for content in message['content'] | selectattr('type'... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ["vision", "image-text-to-text"]} | # LLaVa-Next, leveraging [liuhaotian/llava-v1.6-vicuna-13b](https://huggingface.co/liuhaotian/llava-v1.6-vicuna-13b) as LLM
The LLaVA-NeXT model was proposed in [LLaVA-NeXT: Improved reasoning, OCR, and world knowledge](https://llava-vl.github.io/blog/2024-01-30-llava-next/) by Haotian Liu, Chunyuan Li, Yuheng Li, Bo ... | null | [
"llama2"
] | null | [
"en"
] | 13,351,499,776 | null | null | [
"AutoModelForImageTextToText",
"LlavaNextForConditionalGeneration",
"llava_next"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
669c043b52cf1c619d8d8962 | c1b718d8c9016487 | c81b23e1dcb12302 | 50,280 | BPE | 50,009 | true | true | true | true | 28 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 295 | allenai/OLMoE-1B-7B-0924 | allenai | null | 33,745 | 797,935 | False | 2024-07-20T18:38:51Z | 2024-10-19T04:24:22Z | transformers | 143 | 1 | null | text-generation | null | [
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"README.md",
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"model.safetensors.index.json",
"olmoe-logo.png",
"special_tokens_map.json",
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"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["allenai/OLMoE-mix-0924"], "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": null, "tags": ["moe", "olmo", "olmoe"], "co2_eq_emissions": 1} | <img alt="OLMoE Logo." src="olmoe-logo.png" width="250px">
# Model Summary
> OLMoE-1B-7B is a Mixture-of-Experts LLM with 1B active and 7B total parameters released in September 2024 (0924). It yields state-of-the-art performance among models with a similar cost (1B) and is competitive with much larger models like L... | null | [
"apache-2.0"
] | [
"allenai/OLMoE-mix-0924"
] | [
"en"
] | null | null | null | [
"OlmoeForCausalLM",
"olmoe",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66e98a4ae3e3991610b54d00 | 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-AWQ | Qwen | {
"models": [
{
"_id": "66e81cdaa3681387ffc12b55",
"id": "Qwen/Qwen2.5-14B-Instruct"
}
],
"relation": "quantized"
} | 1,951,930 | 4,630,832 | False | 2024-09-17T13:55:22Z | 2024-10-09T12:26:42Z | transformers | 29 | 1 | null | text-generation | {"parameters": {"I32": 13212057600, "F16": 1557976064}, "total": 14770033664} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
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"tokenizer.json",
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"vocab.json"... | 539535859b135b0244c91f3e59816150c8056698 | [
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"text-generation",
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"license:apache-2.0",
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"endpoints_compati... | 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/Qwen2.5-14B-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-AWQ/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_... | # Qwen2.5-14B-Instruct-AWQ
## 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 **more... | null | [
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"https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-AWQ/blob/main/LICENSE"
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"Qwen2ForCausalLM",
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] | [
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"text"
] | [
"text"
] |
67a41c6e25f2892fafad58a1 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
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"id": "Qwen/Qwen2.5-3B-Instruct"
}
],
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} | 131,607 | 1,060,126 | False | 2025-02-06T02:20:30Z | 2025-02-06T03:39:37Z | transformers | 7 | 0 | null | text-generation | {"parameters": {"F32": 223056, "BF16": 514306048, "U8": 2652079768}, "total": 3166608872} | [
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"4-... | 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",
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<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-4bit"... | null | [
"apache-2.0"
] | null | [
"en"
] | 3,166,608,872 | null | null | [
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6508e5f8c9aa376f76a6c256 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
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"id": "meta-llama/Llama-2-70b-chat-hf"
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],
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} | 1,857 | 1,009,657 | False | 2023-09-19T00:06:16Z | 2023-11-09T18:21:09Z | transformers | 24 | 0 | null | text-generation | {"parameters": {"I32": 68451041280, "F16": 525606912}, "total": 68976648192} | [
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<!-- 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 | [
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} | null | ----------------|----------------|-------------|----------|---------|
| KLUE-BERT-base | 768 | 768 | 12 | 12 |
| KLUE-RoBERTa-base | 768 | 768 | 12 | 12 |
> **Warning** <br>
> Large pre-trained models need a lot of GPU memory to train
## D... | null | null | null | null | 110,618,626 | null | null | [
"roberta",
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65b18f46fcead433ff02d2d1 | 8d65f5c6196e7473 | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
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] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 423 | Salesforce/SFR-Embedding-Mistral | Salesforce | null | 12,079 | 921,036 | False | 2024-01-24T22:29:26Z | 2025-02-04T21:01:42Z | sentence-transformers | 297 | 0 | [{"name": "SFR-Embedding-Mistral", "results": [{"task": {"type": "Classification"}, "dataset": {"type": "mteb/amazon_counterfactual", "name": "MTEB AmazonCounterfactualClassification (en)", "config": "en", "split": "test", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205"}, "metrics": [{"type": "accuracy", "value"... | feature-extraction | {"parameters": {"F16": 7110660096}, "total": 7110660096} | [
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} | {"language": ["en"], "license": "cc-by-nc-4.0", "tags": ["mteb", "sentence-transformers", "transformers"], "model-index": [{"name": "SFR-Embedding-Mistral", "results": [{"task": {"type": "Classification"}, "dataset": {"name": "MTEB AmazonCounterfactualClassification (en)", "type": "mteb/amazon_counterfactual", "config"... | <h1 align="center">Salesforce/SFR-Embedding-Mistral</h1>
**SFR-Embedding by Salesforce Research.**
The model is trained on top of [E5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) and [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
This project is for research purp... | null | [
"cc-by-nc-4.0"
] | null | [
"en"
] | 7,110,660,096 | null | null | [
"AutoModel",
"mistral",
"MistralModel"
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"feature-extraction"
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"multimodal"
] | [
"text"
] | [
"embeddings"
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670fd50a1d19395a94e7a5bc | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | mlx-community/Llama-3.1-Nemotron-70B-Instruct-HF-bf16 | mlx-community | {
"models": [
{
"_id": "6709e0d9bb2498474f4e8ee2",
"id": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
}
],
"relation": "finetune"
} | 333 | 682,076 | False | 2024-10-16T15:00:26Z | 2024-10-16T16:29:19Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"README.md",
"config.json",
"model-00001-of-00028.safetensors",
"model-00002-of-00028.safetensors",
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"model-00005-of-00028.safetensors",
"model-00006-of-00028.safetensors",
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... | b5d957522d51878a723b808861121694b1859801 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"nvidia",
"llama3.1",
"mlx",
"conversational",
"en",
"dataset:nvidia/HelpSteer2",
"base_model:nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"base_model:finetune:nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"license:llama3.1",
"text-ge... | 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": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF", "datasets": ["nvidia/HelpSteer2"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "llama3.1", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["nv... | # mlx-community/Llama-3.1-Nemotron-70B-Instruct-HF-bf16
The Model [mlx-community/Llama-3.1-Nemotron-70B-Instruct-HF-bf16](https://huggingface.co/mlx-community/Llama-3.1-Nemotron-70B-Instruct-HF-bf16) was converted to MLX format from [nvidia/Llama-3.1-Nemotron-70B-Instruct-HF](https://huggingface.co/nvidia/Llama-3.1-Ne... | null | [
"llama3.1"
] | [
"nvidia/HelpSteer2"
] | [
"en"
] | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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6878151a2847036511935e0c | 1f077a9a0005c931 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 230 | OpenMed/OpenMed-NER-BloodCancerDetect-ElectraMed-560M | OpenMed | null | 151,724 | 1,587,355 | False | 2025-07-16T21:09:46Z | 2025-08-05T09:43:04Z | transformers | 1 | 0 | null | token-classification | {"parameters": {"BF16": 558843907}, "total": 558843907} | [
".gitattributes",
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"sentencepiece.bpe.model",
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"test_results.json",
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] | 8b388e62475d8897d53ad3ab6bbb3ea0efa5a851 | [
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"cancer",
"clinical-medicine",
"cl",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["XLMRobertaForTokenClassification"], "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": "AutoModelForTokenClassification",
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"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"
] | 558,843,907 | null | null | [
"XLMRobertaForTokenClassification",
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66e81d3d7c39a8b32971fe62 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-Math-1.5B-Instruct | Qwen | {
"models": [
{
"_id": "66e81d379ebf20e0639888fd",
"id": "Qwen/Qwen2.5-Math-1.5B"
}
],
"relation": "finetune"
} | 80,553 | 1,111,037 | False | 2024-09-16T11:57:49Z | 2024-09-23T06:07:25Z | transformers | 54 | 0 | null | text-generation | {"parameters": {"BF16": 1543714304}, "total": 1543714304} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
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"model.safetensors",
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"vocab.json"
] | aafeb0fc6f22cbf0eaeed126eff8be45b0360a35 | [
"transformers",
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"chat",
"conversational",
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"arxiv:2409.12122",
"base_model:Qwen/Qwen2.5-Math-1.5B",
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"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"re... | 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 {{- 'Please reason step by step, an... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-Math-1.5B", "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-Math-1.5B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_t... | # Qwen2.5-Math-1.5B-Instruct
> [!Warning]
> <div align="center">
> <b>
> 🚨 Qwen2.5-Math mainly supports solving English and Chinese math problems through CoT and TIR. We do not recommend using this series of models for other tasks.
> </b>
> </div>
## Introduction
In August 2024, we released the first series of math... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-Math-1.5B-Instruct/blob/main/LICENSE"
] | null | [
"en"
] | 1,543,714,304 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64197c9e3c73fa42caed8aa2 | d69c589accf1778c | 9cede39e4b3a7ae8 | 50,344 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 144 | google/pix2struct-docvqa-base | google | null | 2,872 | 688,484 | False | 2023-03-21T09:45:02Z | 2023-12-24T21:14:26Z | transformers | 44 | 0 | null | visual-question-answering | {"parameters": {"F32": 282285696}, "total": 282285696} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
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"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | 63f6b3de436e39f75c7a486881a9c2c14a7f4e89 | [
"transformers",
"pytorch",
"safetensors",
"pix2struct",
"image-text-to-text",
"visual-question-answering",
"en",
"fr",
"ro",
"de",
"multilingual",
"arxiv:2210.03347",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["Pix2StructForConditionalGeneration"], "model_type": "pix2struct", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "fr", "ro", "de", "multilingual"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "visual-question-answering", "tags": null, "inference": false... | # Model card for Pix2Struct - Finetuned on Doc-VQA (Visual Question Answering over scanned documents)
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Using the model](#using-the-model)
2. [Contribution](#contrib... | null | [
"apache-2.0"
] | null | [
"en",
"fr",
"ro",
"de",
"multilingual"
] | 282,285,696 | null | null | [
"AutoModelForImageTextToText",
"Pix2StructForConditionalGeneration",
"pix2struct"
] | [
"image-text-to-text",
"visual-question-answering"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text",
"logits"
] |
681feb48cce07fc7766a6921 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | fancyfeast/llama-joycaption-beta-one-hf-llava | fancyfeast | {
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{
"_id": "67b3a208477192f1277fb6a3",
"id": "google/siglip2-so400m-patch14-384"
}
],
"relation": "finetune"
} | 60,184 | 1,031,591 | False | 2025-05-11T00:11:52Z | 2025-05-16T04:12:26Z | transformers | 330 | 3 | null | image-text-to-text | {"parameters": {"BF16": 8479990848}, "total": 8479990848} | [
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"model.safetenso... | ebf414ea497a020da0f82df3913e5b6cb8e9663a | [
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"base_model:finetune:google/siglip2-so400m-patch14-384",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlavaForConditionalGeneration"], "model_type": "llava", "processor_config": {"chat_template": "{%- if not date_string is defined %}\n {%- set date_string = \"26 July 2024\" %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["meta-llama/Llama-3.1-8B-Instruct", "google/siglip2-so400m-patch14-384"], "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": "image-text-to-text", "tag... | # Model Card for Llama JoyCaption Beta One
[Github](https://github.com/fpgaminer/joycaption)
JoyCaption is an image captioning Visual Language Model (VLM) built from the ground up as a free, open, and uncensored model for the community to use in training Diffusion models.
Key Features:
- **Free and Open**: Always re... | null | null | null | null | 8,479,990,848 | null | null | [
"AutoModelForImageTextToText",
"LlavaForConditionalGeneration",
"llava"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
65814fad8ecea67c7d77c41d | c017a519810a367d | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 424 | WizardLMTeam/WizardMath-7B-V1.1 | WizardLMTeam | null | 18,150 | 737,738 | False | 2023-12-19T08:09:17Z | 2024-01-12T11:39:28Z | transformers | 83 | 0 | null | text-generation | null | [
".gitattributes",
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"README.md",
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"pytorch_model-00001-of-00002.bin",
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"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.js... | 1b955017f4f5b5012fb14109740576e34e5268fc | [
"transformers",
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"text-generation",
"en",
"arxiv:2304.12244",
"arxiv:2306.08568",
"arxiv:2308.09583",
"text-generation-inference",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<s>", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"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": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "inference": false} | ## WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct (RLEIF)
<p style="font-size:28px;" align="center">
🏠 <a href="https://wizardlm.github.io/" target="_blank">Home Page</a> </p>
<p align="center">
<p align="center">
🤗 <a href="https://huggingface.co/WizardLM" targe... | null | null | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65853fcc0292cbbde25e1037 | d04663a419a2251e | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 425 | Dongjin-kr/ko-reranker | Dongjin-kr | null | 10,997 | 730,316 | False | 2023-12-22T07:50:36Z | 2025-01-13T00:30:59Z | transformers | 70 | 0 | null | text-classification | {"parameters": {"F32": 559891457}, "total": 559891457} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 8c2ab1a833734491fd3158164dd2b7d8b28e071c | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"text-classification",
"ko",
"en",
"arxiv:2307.03172",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"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"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ko", "en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": null} | # Korean Reranker Training on Amazon SageMaker
### **한국어 Reranker** 개발을 위한 파인튜닝 가이드를 제시합니다.
ko-reranker는 [BAAI/bge-reranker-larger](https://huggingface.co/BAAI/bge-reranker-large) 기반 한국어 데이터에 대한 fine-tuned model 입니다. <br>
보다 자세한 사항은 [korean-reranker-git](https://github.com/aws-samples/aws-ai-ml-workshop-kr/tree/master... | null | [
"mit"
] | null | [
"ko",
"en"
] | 559,891,457 | null | null | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66eaa05b64583d8d2f729e83 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-Coder-1.5B-Instruct | Qwen | {
"models": [
{
"_id": "66eaa052d25d383ddb9a6c5f",
"id": "Qwen/Qwen2.5-Coder-1.5B"
}
],
"relation": "finetune"
} | 837,537 | 3,681,979 | False | 2024-09-18T09:41:47Z | 2025-01-12T02:05:01Z | transformers | 110 | 1 | null | text-generation | {"parameters": {"BF16": 1543714304}, "total": 1543714304} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 2e1fd397ee46e1388853d2af2c993145b0f1098a | [
"transformers",
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"text-generation",
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"codeqwen",
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"qwen",
"qwen-coder",
"conversational",
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"base_model:finetune:Qwen/Qwen2.5-Coder-1.5B",
"license:apache-2.0",
"tex... | 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-Coder-1.5B"], "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-1.5B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeli... | # Qwen2.5-Coder-1.5B-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
Qwen2.5-Coder is the latest series of... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct/blob/main/LICENSE"
] | null | [
"en"
] | 1,543,714,304 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6684ded0502121ba243dc8ed | 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-it-bnb-4bit | unsloth | {
"models": [
{
"_id": "667928d58601cd537f63c846",
"id": "google/gemma-2-9b-it"
}
],
"relation": "quantized"
} | 15,693 | 774,296 | False | 2024-07-03T05:17:04Z | 2024-11-22T08:17:03Z | transformers | 30 | 0 | null | text-generation | {"parameters": {"F32": 588000, "BF16": 918109696, "U8": 8583810488}, "total": 9502508184} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 27b027bcbb6b1861b02551d5c699d5d07f29610a | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"unsloth",
"gemma",
"google",
"conversational",
"en",
"base_model:google/gemma-2-9b-it",
"base_model:quantized:google/gemma-2-9b-it",
"license:gemma",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes... | null | {"architectures": ["Gemma2ForCausalLM"], "model_type": "gemma2", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not s... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "google/gemma-2-9b-it", "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"]} | # Finetune Gemma, Llama 3, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a Google Colab Tesla T4 notebook for **Gemma 2 (9B)** here: https://colab.research.google.com/drive/1vIrqH5uYDQwsJ4-OO3DErvuv4pBgVwk4?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%... | null | [
"gemma"
] | null | [
"en"
] | 9,502,508,184 | null | null | [
"AutoModelForCausalLM",
"gemma2",
"Gemma2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6722d29f02e2f9ded982cdaf | bafc5e0c20be7cd8 | 82d3db801e5d7f68 | 49,152 | BPE | 48,900 | false | true | false | true | 17 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 115 | HuggingFaceTB/SmolLM2-360M | HuggingFaceTB | null | 67,612 | 949,224 | False | 2024-10-31T00:43:11Z | 2025-02-06T10:34:16Z | transformers | 88 | 0 | null | text-generation | {"parameters": {"BF16": 361821120}, "total": 361821120} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | f8027fd0eaeea54caa13c31d31b9fdc459c38b49 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"en",
"arxiv:2502.02737",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_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": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # SmolLM2
## Table of Contents
1. [Model Summary](##model-summary)
2. [Limitations](##limitations)
3. [Training](##training)
4. [License](##license)
5. [Citation](##citation)
## Model Summary
Sm... | null | [
"apache-2.0"
] | null | [
"en"
] | 361,821,120 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64248e56ecb4ee8275ea4e42 | d466f6049e8369e1 | a0788c55db6a1fdb | 1,024 | BPE | 766 | false | true | true | true | 2 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 426 | hf-tiny-model-private/tiny-random-OPTForCausalLM | hf-tiny-model-private | null | 2,503 | 674,373 | False | 2023-03-29T19:15:34Z | 2023-03-29T19:15:38Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"config.json",
"generation_config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 7641dd66056bcf415bf3a536b71c524f07e1f0d3 | [
"transformers",
"pytorch",
"tf",
"opt",
"text-generation",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["OPTForCausalLM"], "model_type": "opt", "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": fa... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"OPTForCausalLM",
"AutoModelForCausalLM",
"opt"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66f4afda60dfe25909a15658 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | mlx-community/Llama-3.2-3B-Instruct-8bit | mlx-community | null | 10,753 | 746,979 | False | 2024-09-26T00:50:34Z | 2024-09-26T01:09:41Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"F16": 100568064, "U32": 803143680}, "total": 903711744} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | ff054899609078569493def2823f9acd2780c0c9 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"mlx",
"conversational",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"license:llama3.2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:u... | 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": null, "datasets": null, "eval_results": null, "language": ["en", "de", "fr", "it", "pt", "hi", "es", "th"], "library_name": "transformers", "license": "llama3.2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["facebook", "meta... | # mlx-community/Llama-3.2-3B-Instruct-8bit
The Model [mlx-community/Llama-3.2-3B-Instruct-8bit](https://huggingface.co/mlx-community/Llama-3.2-3B-Instruct-8bit) was converted to MLX format from [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) using mlx-lm version **0.17.1**.
... | null | [
"llama3.2"
] | null | [
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th"
] | 903,711,744 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64a2c85cda59c4cc017e3eb8 | cb3f886e13ad7505 | 1f1d26e73b02d1f3 | 49,152 | BPE | 48,891 | false | true | false | true | 19 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 70 | bigcode/starcoderbase-1b | bigcode | null | 4,245 | 704,533 | auto | 2023-07-03T13:08:44Z | 2023-09-14T12:49:54Z | transformers | 98 | 0 | [{"name": "StarCoderBase-1B", "results": [{"task": {"type": "text-generation"}, "dataset": {"type": "openai_humaneval", "name": "HumanEval"}, "metrics": [{"name": "pass@1", "type": "pass@1", "value": 15.17, "verified": false}]}, {"task": {"type": "text-generation"}, "dataset": {"type": "nuprl/MultiPL-E", "name": "Multi... | text-generation | {"parameters": {"F32": 1137207296}, "total": 1137207296} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 182f0165fdf8da9c9935901eec65c94337f01c11 | [
"transformers",
"pytorch",
"safetensors",
"gpt_bigcode",
"text-generation",
"code",
"dataset:bigcode/the-stack-dedup",
"arxiv:1911.02150",
"arxiv:2205.14135",
"arxiv:2207.14255",
"arxiv:2305.06161",
"license:bigcode-openrail-m",
"model-index",
"text-generation-inference",
"endpoints_comp... | null | {"architectures": ["GPTBigCodeForCausalLM"], "model_type": "gpt_bigcode", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["bigcode/the-stack-dedup"], "library_name": "transformers", "license": "bigcode-openrail-m", "metrics": ["code_eval"], "pipeline_tag": "text-generation", "tags": ["code"], "inference": true, "widget": [{"text": "def print_hello_world():", "example_title": "Hello world", "group": "Python"}], "extra_gated_p... | null | null | [
"bigcode-openrail-m"
] | [
"bigcode/the-stack-dedup"
] | null | 1,137,207,296 | null | [
"code_eval"
] | [
"gpt_bigcode",
"AutoModelForCausalLM",
"GPTBigCodeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1767f1 | 2e1ee15e476b957a | 22f681e83c875e53 | 31,748 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 427 | Maltehb/danish-bert-botxo | Maltehb | null | 5,076 | 679,774 | False | 2022-03-02T23:29:04Z | 2023-02-07T07:07:47Z | transformers | 14 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.ckpt.data-00000-of-00001",
"model.ckpt.index",
"model.ckpt.meta",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | aeffe01ee981726b623f33ae778187328222ec97 | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"danish",
"masked-lm",
"Certainly",
"fill-mask",
"da",
"dataset:common_crawl",
"dataset:wikipedia",
"dataset:dindebat.dk",
"dataset:hestenettet.dk",
"dataset:danishOpenSubtitles",
"license:cc-by-4.0",
"endpoint... | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "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"
} | {"base_model": null, "datasets": ["common_crawl", "wikipedia", "dindebat.dk", "hestenettet.dk", "danishOpenSubtitles"], "eval_results": null, "language": "da", "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "fill-mask", "tag... | # Danish BERT (version 2, uncased) by [Certainly](https://certainly.io/) (previously known as BotXO).
All credit goes to [Certainly](https://certainly.io/) (previously known as BotXO), who developed Danish BERT. For data and training details see their [GitHub repository](https://github.com/certainlyio/nordic_bert) or ... | null | [
"cc-by-4.0"
] | [
"common_crawl",
"wikipedia",
"dindebat.dk",
"hestenettet.dk",
"danishOpenSubtitles"
] | [
"da"
] | null | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"fill-mask",
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
62ca0895d7aabb0cfd88260b | 2640efa3e653679f | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 428 | pszemraj/grammar-synthesis-small | pszemraj | null | 2,117 | 682,140 | False | 2022-07-09T23:00:37Z | 2025-12-29T03:39:24Z | transformers | 12 | 0 | null | null | {"parameters": {"F32": 76961152}, "total": 76961152} | [
".gitattributes",
"README.md",
"config.json",
"grammar-synthesis-small-WIP-ft3-jflAUG-v5_training_metadata.json",
"model.onnx",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json"
] | 87b056e0099386da1355a3b80e51e59e9faf1219 | [
"transformers",
"pytorch",
"onnx",
"safetensors",
"t5",
"text2text-generation",
"grammar",
"spelling",
"punctuation",
"error-correction",
"grammar synthesis",
"FLAN",
"dataset:jfleg",
"arxiv:2107.06751",
"license:cc-by-nc-sa-4.0",
"license:apache-2.0",
"text-generation-inference",
... | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["jfleg"], "eval_results": null, "language": null, "library_name": null, "license": ["cc-by-nc-sa-4.0", "apache-2.0"], "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["grammar", "spelling", "punctuation", "error-correction"... | # grammar-synthesis-small (beta)
This model is a fine-tuned version of [google/t5-small-lm-adapt](https://huggingface.co/google/t5-small-lm-adapt) for grammar correction on an expanded version of the [JFLEG](https://paperswithcode.com/dataset/jfleg) dataset.
usage in Python (after `pip install transformers`):
```pyt... | null | [
"cc-by-nc-sa-4.0",
"apache-2.0"
] | [
"jfleg"
] | null | 76,961,152 | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
6462ff38904bbc4cf2e5419b | dccbb7b59eac010e | daab2a732bab72e2 | 128,001 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Strip",
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 159 | nightdessert/WeCheck | nightdessert | null | 28 | 667,407 | False | 2023-05-16T03:57:44Z | 2023-05-18T06:42:14Z | transformers | 2 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"pytorch_model.bin",
"spm.model",
"tokenizer.json",
"tokenizer_config.json"
] | 71199c2d1ac86ad4195e0545a584613eaa8ae787 | [
"transformers",
"pytorch",
"deberta-v2",
"text-classification",
"text-generation",
"arxiv:2212.10057",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DebertaV2ForSequenceClassification"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "eos_token": "[SEP]", "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"
} | {"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": "text-generation", "tags": null} | # Factual Consistency Evaluator/Metric in ACL 2023 paper
*[WeCheck: Strong Factual Consistency Checker via Weakly Supervised Learning
](https://arxiv.org/abs/2212.10057)*
Open-sourced code: https://github.com/nightdessert/WeCheck
## Model description
WeCheck is a factual consistency metric trained from weakly annotat... | null | null | null | null | null | null | null | [
"AutoModelForSequenceClassification",
"deberta-v2",
"DebertaV2ForSequenceClassification"
] | [
"text-classification",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"logits",
"text"
] |
687a0d1db0cfcaff8d9ba3b3 | afcb510cd7ee6b0c | 8a01c02d4d0a401c | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 429 | OpenMed/OpenMed-NER-PathologyDetect-TinyMed-135M | OpenMed | null | 187,366 | 1,909,055 | False | 2025-07-18T09:00:13Z | 2025-08-05T09:45:27Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 134736387}, "total": 134736387} | [
".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"
] | 660c7acad93bf8c20a75861cfaee268cae24cd24 | [
"transformers",
"safetensors",
"distilbert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"disease-entity-recognition",
"medical-diagnosis",
"ncbi",
"pathology",
"disease",
"en",
"arxiv:2508.01630",
"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": 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... | # 🧬 [OpenMed-NER-PathologyDetect-TinyMed-135M](https://huggingface.co/OpenMed/OpenMed-NER-PathologyDetect-TinyMed-135M)
**Specialized model for Disease Entity Recognition - Disease entities from the NCBI dataset**
[](https://opensource.org/license... | null | [
"apache-2.0"
] | null | [
"en"
] | 134,736,387 | null | null | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
68da3ab4eea24d7923cb2819 | 0fbdb3abe17d0d5f | b02c1908f37c4055 | 151,365 | BPE | 318,088 | false | true | true | true | 36 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 320 | zai-org/GLM-4.6-FP8 | zai-org | null | 12,080 | 1,152,358 | False | 2025-09-29T07:52:20Z | 2025-10-16T08:18:16Z | transformers | 98 | 0 | null | text-generation | null | [
".gitattributes",
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"chat_template.jinja",
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"model-00001-of-00092.safetensors",
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"model-00006-of-00092... | c064d336a8d0b0f59071f77eafdcdfca40f4b54c | [
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"en",
"zh",
"arxiv:2508.06471",
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"endpoints_compatible",
"compressed-tensors",
"deploy:azure",
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] | null | {"architectures": ["Glm4MoeForCausalLM"], "model_type": "glm4_moe", "quantization_config": {"quant_method": "compressed-tensors"}, "tokenizer_config": {"eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}, "chat_template_jinja": "[gMASK]<sop>\n{%- if tools -%}\n<|system|>\n# Tools\n\nYou may call one or more fun... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "zh"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | null | null | [
"mit"
] | null | [
"en",
"zh"
] | null | null | null | [
"AutoModelForCausalLM",
"Glm4MoeForCausalLM",
"glm4_moe"
] | [
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"text"
] | [
"text"
] | [
"text"
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66034ec09b43d04417fd3e35 | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 106 | google/gemma-1.1-7b-it | google | null | 13,739 | 740,999 | manual | 2024-03-26T22:40:00Z | 2024-06-27T14:09:53Z | transformers | 275 | 0 | null | text-generation | {"parameters": {"BF16": 8537680896}, "total": 8537680896} | [
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"... | 065a528791af6f57f013e8e42b7276992b45ef71 | [
"transformers",
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"gemma",
"text-generation",
"conversational",
"arxiv:2312.11805",
"arxiv:2009.03300",
"arxiv:1905.07830",
"arxiv:1911.11641",
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"arxiv:1907.10641",
"arxiv:1811.00937",
"arxiv:1809.02789",
"arxiv:1911.01547",
"arxiv:17... | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "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": 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... | null | null | [
"gemma"
] | null | null | 8,537,680,896 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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6644c09f4e52ac200d6c1acf | 93330b832a45c4d2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 430 | LazarusNLP/all-indo-e5-small-v4 | LazarusNLP | null | 246,170 | 2,011,622 | False | 2024-05-15T14:03:11Z | 2026-01-21T00:57:56Z | sentence-transformers | 13 | 0 | null | sentence-similarity | {"parameters": {"F32": 117653760}, "total": 117653760} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"onnx/model.onnx",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | ac1d8e6328f8167079ea3b2ba078583f77a2e40a | [
"sentence-transformers",
"onnx",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"dataset:indonli",
"dataset:indolem/indo_story_cloze",
"dataset:unicamp-dl/mmarco",
"dataset:miracl/miracl",
"dataset:nthakur/swim-ir-monolingual",
"dataset:LazarusNLP/multili... | null | {"architectures": ["BertModel"], "model_type": "bert", "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": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["indonli", "indolem/indo_story_cloze", "unicamp-dl/mmarco", "miracl/miracl", "nthakur/swim-ir-monolingual", "LazarusNLP/multilingual-NLI-26lang-2mil7-id", "SEACrowd/wrete", "SEACrowd/indolem_ntp", "khalidalt/tydiqa-goldp", "SEACrowd/facqa", "indonesian-nlp/lfqa_id", "jakartaresearch/in... | # LazarusNLP/all-indo-e5-small-v4
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 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 ... | null | null | [
"indonli",
"indolem/indo_story_cloze",
"unicamp-dl/mmarco",
"miracl/miracl",
"nthakur/swim-ir-monolingual",
"LazarusNLP/multilingual-NLI-26lang-2mil7-id",
"SEACrowd/wrete",
"SEACrowd/indolem_ntp",
"khalidalt/tydiqa-goldp",
"SEACrowd/facqa",
"indonesian-nlp/lfqa_id",
"jakartaresearch/indoqa",
... | null | 117,653,760 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
68781327d4d3cb370d0ebe54 | 6a67cbd79bab1e59 | cf1efbe71ef28fc9 | 50,368 | BPE | 50,009 | true | true | true | true | 116 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 395 | OpenMed/OpenMed-NER-ChemicalDetect-ModernMed-395M | OpenMed | null | 187,900 | 1,902,749 | False | 2025-07-16T21:01:27Z | 2025-08-05T09:42:30Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 395834371}, "total": 395834371} | [
".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"
] | 44731cb969caa7f5c1eacbe748ff2e246db12e0a | [
"transformers",
"safetensors",
"modernbert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"chemical-entity-recognition",
"drug-discovery",
"pharmacology",
"chemistry",
"chem",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ModernBertForTokenClassification"], "model_type": "modernbert", "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"
] | 395,834,371 | null | null | [
"AutoModelForTokenClassification",
"ModernBertForTokenClassification",
"modernbert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66b0f9f15cb4654fd1d665bf | 5d03cb71cd2e2eff | ffd81066dc802081 | 128,259 | BPE | 280,147 | false | true | true | true | 259 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 431 | HuggingFaceM4/Idefics3-8B-Llama3 | HuggingFaceM4 | null | 178,456 | 1,292,245 | False | 2024-08-05T16:12:33Z | 2024-12-02T09:35:34Z | transformers | 302 | 0 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"chat_template.json",
"config.json",
"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",
"preprocessor_config.json"... | fddb4ff79181e55a994674777e06cd5456ce3dc3 | [
"transformers",
"safetensors",
"idefics3",
"image-text-to-text",
"multimodal",
"vision",
"conversational",
"en",
"dataset:HuggingFaceM4/OBELICS",
"dataset:HuggingFaceM4/the_cauldron",
"dataset:HuggingFaceM4/Docmatix",
"dataset:HuggingFaceM4/WebSight",
"arxiv:2306.16527",
"arxiv:2405.02246"... | null | {"architectures": ["Idefics3ForConditionalGeneration"], "model_type": "idefics3", "processor_config": {"chat_template": "<|begin_of_text|>{% for message in messages %}{{message['role'].capitalize()}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": ["HuggingFaceM4/OBELICS", "HuggingFaceM4/the_cauldron", "HuggingFaceM4/Docmatix", "HuggingFaceM4/WebSight"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null... | <p align="center">
<img src="https://huggingface.co/HuggingFaceM4/idefics-80b/resolve/main/assets/IDEFICS.png" alt="Idefics-Obelics logo" width="200" height="100">
</p>
**Transformers version**: >4.46.
# Idefics3
Idefics3 is an open multimodal model that accepts arbitrary sequences of image and text inputs and p... | null | [
"apache-2.0"
] | [
"HuggingFaceM4/OBELICS",
"HuggingFaceM4/the_cauldron",
"HuggingFaceM4/Docmatix",
"HuggingFaceM4/WebSight"
] | [
"en"
] | null | null | null | [
"AutoModelForImageTextToText",
"Idefics3ForConditionalGeneration",
"idefics3"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
66c6b340c797952bc21c4e05 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | alicekyting/Qwen2-Audio-7B-Instruct-4bit | alicekyting | null | 40 | 660,328 | False | 2024-08-22T03:40:48Z | 2024-08-22T11:58:43Z | transformers | 7 | 0 | null | null | {"parameters": {"F32": 111106576, "F16": 1286701056, "U8": 7110461602}, "total": 8508269234} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"preprocessor_config.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 06f5614651eef6e8c1cc5ddb3adcf40d44a998f0 | [
"transformers",
"safetensors",
"qwen2_audio",
"text2text-generation",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["Qwen2AudioForConditionalGeneration"], "model_type": "qwen2_audio", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != ... | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoProcessor"
} | {"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": []} | # Model Card for Model ID
This model is a 4-bit quantized version of Qwen2-Audio-7B-Instruct.
(https://huggingface.co/Qwen/Qwen2-Audio-7B-Instruct)
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed ... | null | null | null | null | 8,508,269,234 | null | null | [
"AutoModelForSeq2SeqLM",
"qwen2_audio",
"Qwen2AudioForConditionalGeneration"
] | [
"text2text-generation"
] | null | null | null |
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