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## This is an experiment on fixing models with incorrect behaviors.
This experiment serves to test and refine a specific training and evaluation pipeline research framework. Its primary objective is to... | null | [
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## Abstract
We present cat llama3 instruct, a llama 3 70b finetuned model focusing on system prompt fidelity, helpfulness and character engagement. The model aims to respect system prompt to an extreme degree, and provide helpful information regardless of situations and offer maximum character imm... | null | [
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**SFR-Embedding by Salesforce Research.**
The Salesforce/SFR-Embedding-Code is a generalist embedding model family for multilingual and multi-task code and Text retrieval. It demonstrates superior performance compared to various open-source code embedding m... | null | [
"cc-by-nc-4.0"
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] | 241 | deepseek-ai/deepseek-coder-33b-base | deepseek-ai | null | 3,107 | 103,341 | False | 2023-10-28T08:14:27Z | 2024-03-07T13:24:08Z | transformers | 75 | 0 | null | text-generation | {"parameters": {"BF16": 33342991360}, "total": 33342991360} | [
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<img width="1000px" alt="DeepSeek Coder" src="https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/pictures/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://coder.deepseek.com/">[🤖 Chat with DeepSeek Coder]</a> | <a href="https... | null | [
"other",
"deepseek-license",
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{
"_id": "65b53851e602b6c2c96e78da",
"id": "BAAI/bge-m3"
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],
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"transformers",
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] | 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",
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} | {"base_model": ["BAAI/bge-m3"], "datasets": null, "eval_results": null, "language": ["vi"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": ["transformers", "cross-encoder", "rerank"]... | # Reranker
* [Usage](#usage)
* [Using FlagEmbedding](#using-flagembedding)
* [Using Huggingface transformers](#using-huggingface-transformers)
* [Fine tune](#fine-tune)
* [Data format](#data-format)
* [Performance](#performance)
* [Contact](#contact)
* [Support The Project](#support-the-project)
* [Citatio... | null | [
"apache-2.0"
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["shanchen/llama3-8B-slerp-med-chinese", "shenzhi-wang/Llama3-8B-Chinese-Chat"], "datasets": null, "eval_results": null, "language": ["zh", "en"], "library_name": null, "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["me... | # llama3-8B-slerp-biomed-chat-chinese
llama3-8B-slerp-biomed-chat-chinese is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [shanchen/llama3-8B-slerp-med-chinese](https://huggingface.co/shanchen/llama3-8B-slerp-med-chinese)... | null | [
"llama3"
] | null | [
"zh",
"en"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6838fdc118b7802951981df0 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | XiaomiMiMo/MiMo-VL-7B-RL | XiaomiMiMo | {
"models": [
{
"_id": "6838fdc118b7802951981df0",
"id": "XiaomiMiMo/MiMo-VL-7B-RL"
}
],
"relation": "finetune"
} | 2,017 | 99,502 | False | 2025-05-30T00:37:21Z | 2025-06-07T06:09:22Z | transformers | 169 | 0 | null | image-text-to-text | {"parameters": {"BF16": 8306217216}, "total": 8306217216} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.json",
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"model.safetensors.in... | 460c34be0c6cfe79b6b311647ae9112784f80b73 | [
"transformers",
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"image-text-to-text",
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"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen2_5_VLForConditionalGeneration"], "model_type": "qwen2_5_vl", "processor_config": {"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are MiM... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["XiaomiMiMo/MiMo-VL-7B-RL"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null} | <div align="center">
<picture>
<source srcset="https://github.com/XiaomiMiMo/MiMo-VL/raw/main/figures/Xiaomi_MiMo_darkmode.png?raw=true" media="(prefers-color-scheme: dark)">
<img src="https://github.com/XiaomiMiMo/MiMo-VL/raw/main/figures/Xiaomi_MiMo.png?raw=true" width="60%" alt="Xiaomi-MiMo" />
</picture... | null | [
"mit"
] | null | null | 8,306,217,216 | null | null | [
"qwen2_5_vl",
"AutoModelForImageTextToText",
"Qwen2_5_VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
65feb7a4298176eb217fcc45 | c67ed9877293591c | 7c4c85b636f4813b | 64,000 | BPE | 110,029 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 934 | cloudyu/Yi-34Bx2-MOE-200K | cloudyu | null | 8,511 | 131,724 | False | 2024-03-23T11:06:12Z | 2024-03-25T10:46:33Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"BF16": 60813892608}, "total": 60813892608} | [
".gitattributes",
"200K.jpg",
"README.md",
"config.json",
"model-00001-of-00013.safetensors",
"model-00002-of-00013.safetensors",
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"model-00005-of-00013.safetensors",
"model-00006-of-00013.safetensors",
"model-00007-of-00013.... | f12fadda84277625714741fe44711421300139d5 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"conversational",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{%- for idx in range(0, messages|length) -%}\n{%- if messages[idx]['role'] == 'user' -%}\n{%- if idx > 1 -%}\n{{- bos_token + '[INST] ' + messages[idx]['content'] + ' [/INST]' -}}\n{%- else -%}\... | {
"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": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | try to build a 200K context length MoE Yi based chat model.
[[GGUF 4bit is here ]https://huggingface.co/cloudyu/Yi-34Bx2-MOE-200K-gguf ]
* Metrics
metrics :
code example
```
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import math
##
model_path = "cloudyu/Yi-34... | null | [
"other"
] | null | null | 60,813,892,608 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
639a55047d3aad77cb2809d3 | f119ccc88a489ffa | aa8af6ff55c14796 | 51,865 | BPE | 49,999 | false | true | true | true | 1,608 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 984 | biodatlab/whisper-th-medium-combined | biodatlab | {
"models": [
{
"_id": "63314c44fece0490c3c94e60",
"id": "openai/whisper-medium"
}
],
"relation": "finetune"
} | 1,590 | 103,368 | False | 2022-12-14T22:58:12Z | 2024-02-20T05:08:36Z | transformers | 19 | 0 | [{"name": "Whisper Medium Thai Combined V4 - biodatlab", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_13_0 th", "type": "mozilla-foundation/common_voice_13_0", "config": "th", "split": "test", "args": "th"}, "... | automatic-speech-recognition | {"parameters": {"F16": 816967680}, "total": 816967680} | [
".gitattributes",
".gitignore",
".ipynb_checkpoints/README-checkpoint.md",
"README.md",
"added_tokens.json",
"all_results.json",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"normalizer.json",
"preprocessor_config.json",
"special_tokens_map.json",
"tokenizer.... | eebf84255cc7f242a504f64ec09ec33d32903fe1 | [
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"whisper",
"automatic-speech-recognition",
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"dataset:google/fleurs",
"base_model:openai/whisper-medium",
"base_model:finetune:openai/whisper-medium",
"doi:10.57967/hf/... | 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": "openai/whisper-medium", "datasets": ["mozilla-foundation/common_voice_13_0", "google/fleurs"], "language": ["th"], "library_name": "transformers", "license": "apache-2.0", "metrics": ["wer"], "tags": ["whisper-event", "generated_from_trainer"], "model-index": [{"name": "Whisper Medium Thai Combined V4 -... | <!-- 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. -->
# Whisper Medium (Thai): Combined V3
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/wh... | null | [
"apache-2.0"
] | [
"mozilla-foundation/common_voice_13_0",
"google/fleurs"
] | [
"th"
] | 816,967,680 | null | [
"wer"
] | [
"WhisperForConditionalGeneration",
"whisper",
"AutoModelForSpeechSeq2Seq"
] | [
"automatic-speech-recognition"
] | [
"multimodal"
] | [
"audio"
] | [
"text"
] |
656cd8f3b4020389020599e3 | fa1db2fed73946fc | 2244742552034edc | 32,022 | BPE | 31,757 | true | true | true | true | 22 | Sequence | Sequence | ByteLevel | [] | [
"Split",
"Split",
"Split",
"Split",
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 484 | ise-uiuc/Magicoder-S-DS-6.7B | ise-uiuc | null | 4,743 | 98,394 | False | 2023-12-03T19:37:23Z | 2024-03-06T07:40:23Z | transformers | 205 | 0 | null | text-generation | {"parameters": {"F32": 6740512768}, "total": 6740512768} | [
".gitattributes",
"LICENSE",
"README.md",
"added_tokens.json",
"assets/overview.svg",
"assets/result.png",
"config.json",
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"model-00002-of-00006.safetensors",
"model-00003-of-00006.safetensors",
"model-00004-of-00006.safetensors",
... | b3ed7cb1578a3643ceaf2ebf996a3d8e85f75d8f | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"dataset:ise-uiuc/Magicoder-OSS-Instruct-75K",
"dataset:ise-uiuc/Magicoder-Evol-Instruct-110K",
"arxiv:2312.02120",
"arxiv:2305.06161",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:a... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "chat_template": "{{bos_token}}{{'You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.\n\n'}}\n{... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["ise-uiuc/Magicoder-OSS-Instruct-75K", "ise-uiuc/Magicoder-Evol-Instruct-110K"], "eval_results": null, "language": null, "library_name": "transformers", "license": "other", "license_name": "deepseek", "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-gene... | # 🎩 Magicoder: Source Code Is All You Need
> Refer to our GitHub repo [ise-uiuc/magicoder](https://github.com/ise-uiuc/magicoder/) for an up-to-date introduction to the Magicoder family!
* 🎩**Magicoder** is a model family empowered by 🪄**OSS-Instruct**, a novel approach to enlightening LLMs with open-source code s... | null | [
"other",
"deepseek"
] | [
"ise-uiuc/Magicoder-OSS-Instruct-75K",
"ise-uiuc/Magicoder-Evol-Instruct-110K"
] | null | 6,740,512,768 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66866b55200cde08fe17aaa3 | f38598271d749bfc | f540d0cefa06a5d9 | 100,002 | BPE | 99,757 | true | true | true | true | 2 | Sequence | Sequence | ByteLevel | [] | [
"Split",
"Split",
"Split",
"Split",
"Split",
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 985 | AI-MO/NuminaMath-7B-TIR | AI-MO | {
"models": [
{
"_id": "65c09805ef796a0c7f83784b",
"id": "deepseek-ai/deepseek-math-7b-base"
}
],
"relation": "finetune"
} | 503 | 91,860 | False | 2024-07-04T09:28:53Z | 2024-08-14T14:05:27Z | transformers | 351 | 0 | [{"name": "NuminaMath-7B-TIR", "results": []}] | text-generation | {"parameters": {"BF16": 6910365696}, "total": 6910365696} | [
".gitattributes",
"README.md",
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"thumbnail.png... | cf2aaf3f706eef519a80523e21c655903203e984 | [
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"generated_from_trainer",
"conversational",
"arxiv:2309.17452",
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"base_model:finetune:deepseek-ai/deepseek-math-7b-base",
"license:apache-2.0",
"text-generation-infer... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "chat_template": "{% for message in messages %}{% if (message['role'] == 'system')%}{{ '' }}{% elif (message['role'] == 'user')%}{{ '### Problem: ' + message['content'] + '\n' }}... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "deepseek-ai/deepseek-math-7b-base", "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "NuminaMath-7B-TIR", "pipeline_tag": "text-generation", "tags": ["alignment-handbook", "ge... | <!-- 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. -->
<img src="https://huggingface.co/AI-MO/NuminaMath-7B-TIR/resolve/main/thumbnail.png" alt="Numina Logo" width="800" style="margin-lef... | null | [
"apache-2.0"
] | null | null | 6,910,365,696 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66834f3ff4dd16f51204424e | d2148bb768dcf67e | 664d254b6eeb0893 | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 445 | h2oai/deberta_finetuned_pii | h2oai | null | 5,854 | 109,745 | False | 2024-07-02T00:52:15Z | 2025-02-06T00:12:12Z | transformers | 8 | 0 | null | token-classification | {"parameters": {"F32": 138690932}, "total": 138690932} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"gitattributes",
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"tokenizer_config.json",
"trainer_state.json",
"trai... | 68089cd67db0b937a48ef97b62673cfdde67cb83 | [
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"deberta",
"token-classification",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DebertaForTokenClassification"], "model_type": "deberta", "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": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "token-classification", "tags": null} | A finetuned model designed to recognize and classify Personally Identifiable Information (PII) within unstructured text data. This powerful model accurately identifies a wide range of PII categories, such as account names, credit card numbers, emails, phone numbers, and addresses. The model is specifically trained to d... | null | [
"mit"
] | null | [
"en"
] | 138,690,932 | null | null | [
"DebertaForTokenClassification",
"AutoModelForTokenClassification",
"deberta"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65483559dbce6bd2be2c767d | dd3bf0749afb5b4c | ea6e051246d01ec3 | 36,608 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 941 | OpenBuddy/openbuddy-zephyr-7b-v14.1 | OpenBuddy | null | 767 | 94,433 | False | 2023-11-06T00:37:45Z | 2023-11-07T10:03:09Z | transformers | 50 | 0 | null | text-generation | null | [
".gitattributes",
"Evaluation.txt",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 208b6fb841239a36fb0ea675179a231e0ad9d287 | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru",
"license:apache-2.0",
"text-generation-inference",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "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, "rstr... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh", "en", "fr", "de", "ja", "ko", "it", "ru"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "inference... | # OpenBuddy - Open Multilingual Chatbot
GitHub and Usage Guide: [https://github.com/OpenBuddy/OpenBuddy](https://github.com/OpenBuddy/OpenBuddy)
Website and Demo: [https://openbuddy.ai](https://openbuddy.ai)
Evaluation result of this model: [Evaluation.txt](Evaluation.txt)
![Demo](https://raw.githubusercontent.com/... | null | [
"apache-2.0"
] | null | [
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru"
] | null | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64bf3f3bcf4f379eebdbdcea | c016642a0a032b6a | fd5b32c0da4d4122 | 32,003 | BPE | 61,249 | true | false | true | true | 6 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 545 | HuggingFaceM4/idefics-80b-instruct | HuggingFaceM4 | null | 5,769 | 105,276 | False | 2023-07-25T03:19:23Z | 2023-10-12T18:44:04Z | transformers | 189 | 0 | null | text-generation | null | [
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"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": ["HuggingFaceM4/OBELICS", "wikipedia", "facebook/pmd", "laion/laion2B-en"], "eval_results": null, "language": "en", "library_name": null, "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["mul... | <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>
# IDEFICS
*How do I pronounce the model's name? Watch a [Youtube tutorial](https://www.youtube.com/watch?v=YKO0rWnPN2I&ab_channel=FrenchPronuncia... | null | [
"other"
] | [
"HuggingFaceM4/OBELICS",
"wikipedia",
"facebook/pmd",
"laion/laion2B-en"
] | [
"en"
] | null | null | null | [
"AutoModelForImageTextToText",
"idefics",
"IdeficsForVisionText2Text"
] | [
"image-text-to-text",
"image-to-text",
"text-generation"
] | [
"text",
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
64d9327e5e5f05485c1d8014 | db10cbe7f986673b | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 986 | khhuang/zerofec-qa2claim-t5-base | khhuang | null | 65 | 90,379 | False | 2023-08-13T19:43:58Z | 2023-08-31T18:16:21Z | transformers | 4 | 0 | null | null | {"parameters": {"F32": 222903552}, "total": 222903552} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"optimizer.pt",
"pytorch_model.bin",
"rng_state_0.pth",
"scaler.pt",
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"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json",
"training_args.bin"
] | b31495d5e393fe002348d0d19470184f6bde797c | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"en",
"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": 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": null, "widget": [{"text": "a 1968 american independent horror film \\\\n What is Night of t... | # QA2Claim Model From ZeroFEC
ZeroFEC is a faithful and interpetable factual error correction framework introduced in the paper [Zero-shot Faithful Factual Error Correction](https://aclanthology.org/2023.acl-long.311/). It involves a component that converts qa-pairs to declarative statements, which is hosted in this ... | null | null | null | [
"en"
] | 222,903,552 | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc136468d709f1810fb | 3957bc03710f8413 | 4bea97215fbe3368 | 32,102 | Unigram | null | true | true | true | true | 105 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 987 | tscholak/cxmefzzi | tscholak | null | 345 | 91,004 | False | 2022-03-02T23:29:05Z | 2022-01-10T21:49:50Z | transformers | 32 | 0 | null | null | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"optimizer.pt",
"pytorch_model.bin",
"scheduler.pt",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json",
"training_args.bin"
] | 2899ad9eafd58585ef3cb8634367c404c2d266e9 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"text2sql",
"en",
"dataset:spider",
"arxiv:2109.05093",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
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} | {"base_model": null, "datasets": ["spider"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["spider"], "model_name": null, "pipeline_tag": null, "tags": ["text2sql"], "thumbnail": "https://repository-images.githubuserconte... | ## tscholak/cxmefzzi
Fine-tuned weights for [PICARD - Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models](https://arxiv.org/abs/2109.05093) based on [T5-3B](https://huggingface.co/t5-3b).
### Training Data
The model has been fine-tuned on the 7000 training examples in the [Spider te... | null | [
"apache-2.0"
] | [
"spider"
] | [
"en"
] | null | null | [
"spider"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc136468d709f17d82b | 8fe1584676725578 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 988 | lighteternal/stsb-xlm-r-greek-transfer | lighteternal | null | 1,237 | 92,890 | False | 2022-03-02T23:29:05Z | 2021-10-11T21:16:05Z | sentence-transformers | 6 | 0 | null | sentence-similarity | null | [
".gitattributes",
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"sentence_bert_config.json",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 28e381a9365abcf8ad2c0808532a8b8cf0d48260 | [
"sentence-transformers",
"pytorch",
"xlm-roberta",
"feature-extraction",
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"en",
"el",
"arxiv:2004.09813",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaModel"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": ... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "el"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-... | # Semantic Textual Similarity for the Greek language using Transformers and Transfer Learning
### By the Hellenic Army Academy (SSE) and the Technical University of Crete (TUC)
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and ca... | null | [
"apache-2.0"
] | null | [
"en",
"el"
] | null | null | null | [
"XLMRobertaModel",
"AutoModel",
"xlm-roberta"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
6850a498533e988cf417673d | d29682aa7c7188cd | d059bb6f4b5e0960 | 151,667 | BPE | 151,387 | true | true | true | true | 24 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 989 | nvidia/AceReason-Nemotron-1.1-7B | nvidia | null | 5,051 | 115,094 | False | 2025-06-16T23:11:20Z | 2025-07-11T05:49:43Z | transformers | 57 | 0 | null | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
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"conversational",
"en",
"arxiv:2506.13284",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"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 {{- 'You are a helpful assistant. Y... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "other", "license_name": "nvidia-open-model-license", "license_link": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/", "metrics": null, "model_name": null,... | null | null | [
"other",
"nvidia-open-model-license",
"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/"
] | null | [
"en"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
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"text-generation"
] | [
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"text"
] | [
"text"
] |
666b51040c8ae90e1971e6b9 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | nm-testing/tinyllama-oneshot-w8a8-channel-dynamic-token-v2 | nm-testing | null | 9,364 | 121,591 | False | 2024-06-13T20:05:24Z | 2024-10-09T19:59:15Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 131558400, "I8": 968884224}, "total": 1100442624} | [
".gitattributes",
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] | 4f7f46a464a487f25af248eac26a361c5c29d810 | [
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"text-generation-inference",
"endpoints_compatible",
"8-bit",
"compressed-tensors",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "compressed-tensors"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | 1,100,442,624 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
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"text"
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"text"
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6595d820b02e572eb0b2730a | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | abacusai/Slerp-CM-mist-dpo | abacusai | null | 8,472 | 131,228 | False | 2024-01-03T21:56:48Z | 2024-01-17T14:13:18Z | transformers | 7 | 0 | null | text-generation | {"parameters": {"F16": 7241732096}, "total": 7241732096} | [
".gitattributes",
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"tokenizer_config.... | 4faccd0200c5f95dd791432f80f1cecaccc5e9d1 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"license:apache-2.0",
"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": true}} | {
"auto_model": "AutoModelForCausalLM",
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} | {"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": ["merge"]} | 
This model is a [Slerp Merge](https://github.com/cg123/mergekit/blob/main/mergekit/merge_methods/slerp.py) of [cookinai/CatMacaroni-Slerp](https://huggingface.co/cookinai/CatMacaroni-Slerp) and [mncai... | null | [
"apache-2.0"
] | null | null | 7,241,732,096 | null | null | [
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65212cb28fc4884992be97b6 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
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] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | jphme/em_german_leo_mistral | jphme | null | 776 | 102,807 | False | 2023-10-07T10:02:26Z | 2023-10-27T23:50:35Z | transformers | 73 | 0 | null | text-generation | {"parameters": {"F16": 7241732096}, "total": 7241732096} | [
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] | 4f03ad4ce09f81cdb00e20649cb0c91625fe26ce | [
"transformers",
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"text-generation",
"pytorch",
"german",
"deutsch",
"leolm",
"conversational",
"de",
"license:apache-2.0",
"text-generation-inference",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{% if message['role'] == 'system' %}{{message['content'] + ' '}}{% eli... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["de"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "EM German", "pipeline_tag": "text-generation", "tags": ["pytorch", "german", "deutsch", "mistral", "leolm"... | 
LeoLM Mistral is the showcase-model of the EM German model family and as of its release in our opinion the best open German LLM.
**Many thanks to the [LeoLM](https://huggingface.co/LeoLM) team for the publication of a base model that has received continued pretraining with German te... | null | [
"apache-2.0"
] | null | [
"de"
] | 7,241,732,096 | null | null | [
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] | [
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6718882c9dfd0bb65ca9c8f0 | 934c57a787329844 | 302e80cadffaf147 | 151,343 | BPE | 318,088 | false | true | true | true | 14 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 918 | zai-org/glm-4-9b-chat-hf | zai-org | {
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{
"_id": "665ed7f6a57b277d7a293ed4",
"id": "zai-org/glm-4-9b-chat"
}
],
"relation": "finetune"
} | 37,657 | 181,395 | False | 2024-10-23T05:22:52Z | 2025-01-27T05:26:17Z | transformers | 24 | 0 | null | text-generation | {"parameters": {"BF16": 9399951360}, "total": 9399951360} | [
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] | null | {"architectures": ["GlmForCausalLM"], "model_type": "glm", "tokenizer_config": {"chat_template": "[gMASK]<sop>{% for item in messages %}{% if item['tools'] is defined %}<|system|>\n\u4f60\u662f\u4e00\u4e2a\u540d\u4e3a ChatGLM \u7684\u4eba\u5de5\u667a\u80fd\u52a9\u624b\u3002\u4f60\u662f\u57fa\u4e8e\u667a\u8c31AI\u8bad\u... | {
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} | {"base_model": ["THUDM/glm-4-9b-chat"], "datasets": null, "eval_results": null, "language": ["en", "zh"], "library_name": "transformers", "license": "other", "license_name": "glm-4", "license_link": "https://huggingface.co/THUDM/glm-4-9b-chat-hf/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "... | null | null | [
"other",
"glm-4",
"https://huggingface.co/THUDM/glm-4-9b-chat-hf/blob/main/LICENSE"
] | null | [
"en",
"zh"
] | 9,399,951,360 | null | null | [
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"text"
] | [
"text"
] |
660dc1fc8539fd03915e235a | 02217ffa5907f57a | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 130 | paloalma/ECE-TW3-JRGL-V1 | paloalma | null | 8,441 | 131,074 | False | 2024-04-03T20:54:20Z | 2024-04-19T13:32:48Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F16": 68976648192}, "total": 68976648192} | [
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"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "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/...') }}... | {
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["merge", "mergekit", "ShinojiResearch/Senku-70B-Full", "152334H/miqu-1-70b-sf"]} | # ECE-TW3-JRGL-V1
## This model has been produced by :
- [Louis Garcia](https://www.linkedin.com/in/louis-garcia-profil/), engineering student at [French Engineering School ECE](https://www.ece.fr/en/)
- [Matthieu Jollard](https://www.linkedin.com/in/matthieu-jollard/), engineering student at [French Engineering Scho... | null | [
"apache-2.0"
] | null | null | 68,976,648,192 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65f82746c5906963eb635514 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | automerger/YamshadowExperiment28-7B | automerger | {
"models": [
{
"_id": "65ed161cd767680a0c769244",
"id": "automerger/YamShadow-7B"
},
{
"_id": "65e1e9f1ea75a9d729d42e9f",
"id": "yam-peleg/Experiment28-7B"
}
],
"relation": "merge"
} | 7,981 | 127,891 | False | 2024-03-18T11:36:38Z | 2024-04-08T22:53:09Z | transformers | 23 | 0 | null | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
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"tokenizer.model",
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] | 76972ed8aacba1fd14f78e6f8d347f087f8b6800 | [
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"automerger",
"base_model:automerger/YamShadow-7B",
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"base_model:yam-peleg/Experiment28-7B",
"base_model:merge:yam-peleg/Experiment28-7B",
"license:apa... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<unk>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
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} | {"base_model": ["automerger/YamShadow-7B", "yam-peleg/Experiment28-7B"], "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": ["merge", "mergekit", "lazymerg... | # 🧪 YamshadowExperiment28-7B
**🎉 YamshadowExperiment28-7B is currently the best-performing 7B model on the Open LLM Leaderboard (08 Apr 24). Use it with caution, as it is likely a sign of overfit... | null | [
"apache-2.0"
] | null | null | 7,241,732,096 | null | null | [
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"text"
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681a60a4d52c388aaa9b4aff | 21feada71fab2765 | 12ebeebff692ebb1 | 131,072 | BPE | 269,443 | false | true | true | true | 1,000 | null | Sequence | ByteLevel | null | [
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"ByteLevel"
] | 245 | m8than/Mistral-Nemo-Instruct-2407-lenient-chatfix | m8than | null | 16,023 | 217,270 | False | 2025-05-06T19:19:00Z | 2025-05-07T10:44:18Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 12247782400}, "total": 12247782400} | [
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66e05e3185724b1625fdab13 | c6de6331832e687a | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
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"ByteLevel"
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{
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"id": "meta-llama/Llama-3.1-8B-Instruct"
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} | 1,550 | 98,218 | False | 2024-09-10T14:56:49Z | 2025-01-17T13:49:05Z | transformers | 197 | 0 | [{"name": "Llama-3.1-SuperNova-Lite", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "HuggingFaceH4/ifeval", "args": {"num_few_shot": 0}}, "metrics": [{"type": "inst_level_strict_acc and prompt_level_strict_acc", "value": 80.17, "name": "stric... | text-generation | null | [
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<div align="center">
<img src="https://i.ibb.co/r072p7j/eopi-ZVu-SQ0-G-Cav78-Byq-Tg.png" alt="Llama-3.1-SuperNova-Lite" style="border-radius: 10px; box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.2), 0 6px 20px 0 rgba(0, 0, 0, 0.19); max-width: 100%; height: auto;">
</div>
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## Overview
Llama-3.1-SuperNova-Lite is an... | null | [
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6570b85fc4093bd525b8ffdf | 2cef78fb90b5be2d | 0363d4167c0e2f0e | 32,024 | BPE | 61,260 | true | false | true | true | 15 | Sequence | null | Sequence | [
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} | 12 | 89,598 | False | 2023-12-06T18:07:27Z | 2023-12-10T20:39:03Z | transformers | 1 | 0 | [{"name": "NexusRaven-13B", "results": []}] | text-generation | {"parameters": {"I32": 12687769600, "F16": 328340480}, "total": 13016110080} | [
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} | {"base_model": "Nexusflow/NexusRaven-V2-13B", "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": "NexusRaven-13B", "pipeline_tag": null, "tags": null, "inference": false, "model_creator": "Nexusflow... | <!-- 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 | [
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
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] | 46 | nm-testing/tinyllama-oneshot-w8-channel-a8-tensor | nm-testing | null | 1,635 | 93,709 | False | 2024-06-18T22:01:28Z | 2024-10-09T19:59:16Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 131558554, "I8": 968884224}, "total": 1100442778} | [
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "compressed-tensors"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message... | {
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} | null | null | null | null | null | null | 1,100,442,778 | null | null | [
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680169d4cf63bc131ba188f1 | cdf28af53b0afd34 | 3c94f41626151d20 | 100,352 | BPE | 100,000 | false | true | false | true | 96 | null | Sequence | ByteLevel | null | [
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{
"_id": "67597bd1b9cdca50cb621f94",
"id": "microsoft/phi-4"
}
],
"relation": "finetune"
} | 7,663 | 339,332 | False | 2025-04-17T20:51:32Z | 2025-11-24T17:47:12Z | transformers | 335 | 0 | null | text-generation | null | [
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} | {"base_model": ["microsoft/phi-4"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": "https://huggingface.co/microsoft/Phi-4-reasoning-plus/resolve/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text... | # Phi-4-reasoning-plus Model Card
[Phi-4-reasoning Technical Report](https://huggingface.co/papers/2504.21318)
## Model Summary
| | |
|-------------------------|-------------------------------------------------... | null | [
"mit",
"https://huggingface.co/microsoft/Phi-4-reasoning-plus/resolve/main/LICENSE"
] | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
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"text-generation"
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"text"
] | [
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647dcc5a5214d172cbb54b03 | 23319cd41dac8bf3 | d81d8676ee526b00 | 65,029 | BPE | 64,784 | false | true | false | true | 17 | null | Sequence | ByteLevel | null | [
"Punctuation",
"ByteLevel",
"Digits",
"Split"
] | [
"ByteLevel"
] | 990 | OpenAssistant/falcon-7b-sft-top1-696 | OpenAssistant | null | 30 | 89,410 | False | 2023-06-05T11:51:54Z | 2023-06-06T10:29:02Z | transformers | 22 | 0 | null | text-generation | null | [
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"custom_class": "modelling_RW.RWForCausalLM",
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} | {"base_model": null, "datasets": ["OpenAssistant/oasst1"], "eval_results": null, "language": ["en", "de", "es", "fr"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["sft"], "widget": [... | # Open-Assistant Falcon 7B SFT OASST-TOP1 Model
This model is a fine-tuning of TII's [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b) LLM.
It was trained with 11,123 top-1 (high-quality) demonstrations of the OASST data set (exported on June 2, 2023) with a batch size of 128 for 8 epochs with LIMA style dropout (p... | null | [
"apache-2.0"
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"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
653a77eae81b2b0dfb749530 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | galatolo/cerbero-7b | galatolo | null | 3,478 | 97,328 | False | 2023-10-26T14:30:02Z | 2024-03-29T14:03:32Z | transformers | 14 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
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"tokenizer... | d6f79f011601c00f1daf0847c14fc46860fed8a8 | [
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"dataset:andreabac3/MedQuaAD-Italian-Fauno-Baize",
"arxiv:2311.15698",
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"text-ge... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{bos_token}}{% for message in messages %}{% if message['role'] == 'user' %}{{ '[|Umano|] ' + message['content'] + '\n' }}{% elif message['role'] == 'assistant' %}{{ '[|Assistente|] ' + message[... | {
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} | {"base_model": null, "datasets": ["andreabac3/Quora-Italian-Fauno-Baize", "andreabac3/StackOverflow-Italian-Fauno-Baize", "andreabac3/MedQuaAD-Italian-Fauno-Baize"], "eval_results": null, "language": ["it", "en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null... | # cerbero-7b Italian LLM 🚀
> 🚀 **New Release**: **cerbero-7b-openchat** our latest SOTA model based on [**openchat3.5**](https://github.com/imoneoi/openchat), delivering performance **on par with** or **superior** to **ChatGPT 3.5**!
> 🔥 The research paper unveiling the secrets behind **cerbero-7b** is now availa... | null | [
"apache-2.0"
] | [
"andreabac3/Quora-Italian-Fauno-Baize",
"andreabac3/StackOverflow-Italian-Fauno-Baize",
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Note: 1. Remember to use the formulation of Anthropic/hh-rlhf dataset for infer... | null | [
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. It was trained on [stsb](https://huggingface.co/datasets/stsb_multi_mt/viewer/it/train).
If you lik... | null | null | [
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] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
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- wandb: https://wandb.ai/open-assistant/supervised-finetuning/runs/pcw1ejda
- [sampling report](https://raw.githubusercontent.com/Open-Assistant/oasst-model-eval/main/sampling_reports/oasst-s... | null | [
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] | 995 | tdklab/hebert-finetuned-hebrew-metaphor | tdklab | null | 40 | 89,621 | False | 2023-07-17T07:19:58Z | 2023-10-03T11:43:56Z | transformers | 4 | 0 | [{"name": "hebert-finetuned-hebrew-metaphor", "results": []}] | text-classification | null | [
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The model is fine-tuned to determine if a word in a sentence is used metaphorically or literally.
The model was trained for the following verbs:
לחלום, לחתוך, לעוף, לפרק, להדליק, לכבס, לכופף, לרסק, לבשל, למחוק, לקפוץ, לקרוע, לקצור, לרקוד, לשבור, לשדוד, לשתות, לטחון, לתפור, לזרוע
Th... | null | null | [
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] | 996 | ychenNLP/arabic-ner-ace | ychenNLP | null | 14 | 118,616 | False | 2022-06-29T18:45:26Z | 2022-07-12T20:02:24Z | transformers | 2 | 0 | null | token-classification | null | [
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] | 2ea8baa63841c8f8bec9a1d8204589b951cc7455 | [
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"ar",
"en",
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"endpoints_compatible",
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] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
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} | {"base_model": null, "datasets": ["ACE2005"], "eval_results": null, "language": ["ar", "en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["BERT", "token-classification", "sequence-tagger-model"]} | # Arabic NER Model
- [Github repo](https://github.com/edchengg/GigaBERT)
- NER BIO tagging model based on [GigaBERTv4](https://huggingface.co/lanwuwei/GigaBERT-v4-Arabic-and-English).
- ACE2005 Training data: English + Arabic
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] | 230 | classla/xlm-roberta-base-multilingual-text-genre-classifier | classla | {
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"id": "FacebookAI/xlm-roberta-base"
}
],
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} | 15,445 | 178,239 | False | 2022-11-11T09:33:55Z | 2025-11-19T07:36:47Z | transformers | 30 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 278050569}, "total": 278051083} | [
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6536808362dd8126cf72af9c | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
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"Metaspace"
] | 11 | facebook/musicgen-stereo-small | facebook | null | 2,018 | 98,664 | False | 2023-10-23T14:17:39Z | 2024-03-06T14:41:16Z | transformers | 39 | 0 | null | text-to-audio | {"parameters": {"F16": 607868486}, "total": 607868486} | [
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] | null | {"architectures": ["MusicgenForConditionalGeneration"], "model_type": "musicgen", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
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"pipeline_tag": "text-to-audio",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-to-audio", "tags": ["musicgen", "audiocraft"], "inference": true, "widget": [{"... | # MusicGen - Stereo - Small - 300M
We further release a set of stereophonic capable models. Those were fine tuned for 200k updates starting
from the mono models. The training data is otherwise identical and capabilities and limitations are shared with the base modes. The stereo models work by getting 2 streams of toke... | null | [
"cc-by-nc-4.0"
] | null | null | 607,868,486 | null | null | [
"musicgen",
"MusicgenForConditionalGeneration",
"AutoModelForTextToWaveform"
] | [
"text-to-audio"
] | [
"text"
] | [
"text"
] | [
"audio"
] |
621ffdc136468d709f181535 | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | voidful/context-only-question-generator | voidful | null | 16 | 88,899 | False | 2022-03-02T23:29:05Z | 2023-03-29T15:40:54Z | transformers | 26 | 0 | null | text-generation | {"parameters": {"F32": 178074201}, "total": 178074201} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 55f2c093bd86e78fdcbd25e62ad856d1be99ecd6 | [
"transformers",
"pytorch",
"safetensors",
"bart",
"text2text-generation",
"question",
"generation",
"seq2seq",
"en",
"dataset:unifiedQA",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BartForConditionalGeneration"], "model_type": "bart", "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": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["unifiedQA"], "eval_results": null, "language": "en", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["bleu", "rouge"], "model_name": null, "pipeline_tag": "text2text-generation", "tags": ["bart", "question", "generation", "seq2seq"], "wid... | # context-only-question-generator
## Model description
This model is a sequence-to-sequence question generator which takes context as an input, and generates a question as an output.
It is based on a pretrained `bart-base` model.
#### How to use
Inputs should be organised into the following format:
```
c... | null | null | [
"unifiedQA"
] | [
"en"
] | 178,074,201 | null | [
"bleu",
"rouge"
] | [
"bart",
"BartForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68926253486177565ffc4f3b | 441f36ff7235b58e | 985b920c8f6b14f1 | 200,019 | BPE | 446,189 | false | true | true | true | 21 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 54 | unsloth/gpt-oss-20b-bnb-4bit | unsloth | {
"models": [
{
"_id": "68913539bd3d0a833438591d",
"id": "openai/gpt-oss-20b"
}
],
"relation": "quantized"
} | 15,873 | 134,822 | False | 2025-08-05T19:58:11Z | 2025-08-06T17:44:41Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"F32": 206112, "BF16": 20277606144, "U8": 656949396}, "total": 20914757184} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model-00001-of-00009.safetensors",
"model-00002-of-00009.safetensors",
"model-00003-of-00009.safetensors",
"model-00004-of-00009.safetensors",
"model-00005-of-00009.safetensors",
"model-00006-of-00009... | 4b7553a5ec02363c3b64433f48cf385fe86b8acd | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"openai",
"unsloth",
"conversational",
"base_model:openai/gpt-oss-20b",
"base_model:quantized:openai/gpt-oss-20b",
"license:apache-2.0",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["GptOssForCausalLM"], "model_type": "gpt_oss", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|return|>", "pad_token": "<|reserved_200017|>", "unk_token": null}, "chat_template_j... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["openai/gpt-oss-20b"], "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": ["openai", "unsloth"]} | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/gpt-oss-6892433695ce0dee42f31681">our collection</a> for all versions of gpt-oss including GGUF, 4-bit & 16-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em>Learn to run gpt-oss c... | null | [
"apache-2.0"
] | null | null | 20,914,757,184 | null | null | [
"AutoModelForCausalLM",
"GptOssForCausalLM",
"gpt_oss"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66ae9f7aa45133da7052db96 | 390af744e5565f11 | 101408923f784238 | 64,000 | WordPiece | null | true | true | true | true | 8 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 924 | Omartificial-Intelligence-Space/GATE-AraBert-v1 | Omartificial-Intelligence-Space | {
"models": [
{
"_id": "66a5e17f8e291e4721b18ae0",
"id": "Omartificial-Intelligence-Space/Arabic-Triplet-Matryoshka-V2"
}
],
"relation": "finetune"
} | 1,196 | 100,317 | False | 2024-08-03T21:22:02Z | 2025-09-07T07:48:11Z | sentence-transformers | 17 | 0 | [{"name": "Omartificial-Intelligence-Space/GATE-AraBert-v1", "results": [{"task": {"type": "STS"}, "dataset": {"name": "MTEB STS17 (ar-ar)", "type": "mteb/sts17-crosslingual-sts", "config": "ar-ar", "split": "test", "revision": "faeb762787bd10488a50c8b5be4a3b82e411949c"}, "metrics": [{"type": "cosine_pearson", "value":... | feature-extraction | {"parameters": {"F32": 135193344}, "total": 135193344} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | c412cd4d9a7f8cb1c16b519a8c47ac9e89a83083 | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"mteb",
"sentence-similarity",
"generated_from_trainer",
"dataset_size:947818",
"loss:SoftmaxLoss",
"loss:CosineSimilarityLoss",
"transformers",
"ar",
"dataset:Omartificial-Intelligence-Space/Arabic-stsb",
"dataset:Omart... | 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": "Omartificial-Intelligence-Space/Arabic-Triplet-Matryoshka-V2", "datasets": ["Omartificial-Intelligence-Space/Arabic-stsb", "Omartificial-Intelligence-Space/Arabic-NLi-Pair-Class"], "language": ["ar"], "library_name": "sentence-transformers", "license": "apache-2.0", "metrics": ["pearson_cosine", "spearm... | # GATE-AraBert-V1
This is **GATE | General Arabic Text Embedding** trained using SentenceTransformers in a **multi-task** setup. The system trains on the **AllNLI** and on the **STS** dataset. It is described in detail in the paper [GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Hybr... | null | [
"apache-2.0"
] | [
"Omartificial-Intelligence-Space/Arabic-stsb",
"Omartificial-Intelligence-Space/Arabic-NLi-Pair-Class"
] | [
"ar"
] | 135,193,344 | null | [
"pearson_cosine",
"spearman_cosine",
"pearson_manhattan",
"spearman_manhattan",
"pearson_euclidean",
"spearman_euclidean",
"pearson_dot",
"spearman_dot",
"pearson_max",
"spearman_max"
] | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
6461d882cf4bf38e231bbcd2 | 1518b5b91df51a3a | 06c049f6287d7099 | 52,000 | BPE | 51,760 | true | true | true | true | 2 | NFKC | ByteLevel | ByteLevel | [
"NFKC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 604 | cyberagent/open-calm-1b | cyberagent | null | 187 | 95,395 | False | 2023-05-15T07:00:18Z | 2023-05-18T01:11:30Z | transformers | 17 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 81340b8150835767036baa4db7ec4b97d92ff2d7 | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"japanese",
"causal-lm",
"ja",
"dataset:wikipedia",
"dataset:cc100",
"dataset:mc4",
"license:cc-by-sa-4.0",
"text-generation-inference",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|padding|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["wikipedia", "cc100", "mc4"], "eval_results": null, "language": ["ja"], "library_name": null, "license": "cc-by-sa-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["japanese", "causal-lm"], "inference": false} | # OpenCALM-1B
## Model Description
OpenCALM is a suite of decoder-only language models pre-trained on Japanese datasets, developed by CyberAgent, Inc.
## Usage
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("cyberagent/open-calm-1b",... | null | [
"cc-by-sa-4.0"
] | [
"wikipedia",
"cc100",
"mc4"
] | [
"ja"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67a3c1427ee49db18c9e9a59 | 27a47e631d8f9d77 | 377ed779fd867883 | 128,257 | BPE | 280,147 | false | true | true | true | 257 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 224 | fixie-ai/ultravox-v0_5-llama-3_1-8b | fixie-ai | null | 3,775 | 106,476 | False | 2025-02-05T19:51:30Z | 2025-05-06T23:23:22Z | transformers | 35 | 0 | null | audio-text-to-text | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"preprocessor_config.json",
"processor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"ultravox_config.py",
"ultravox_model.py",
"ultravox_pipeline.py",
"ultrav... | 94aa77f70ca548e669ea61f737e159b2fddbb7f7 | [
"transformers",
"safetensors",
"ultravox",
"feature-extraction",
"audio-text-to-text",
"custom_code",
"ar",
"be",
"bg",
"bn",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"fi",
"fr",
"gl",
"hi",
"hu",
"it",
"ja",
"ka",
"lt",
"lv",
"mk",
"mr",
"n... | null | {"architectures": ["UltravoxModel"], "auto_map": {"AutoConfig": "ultravox_config.UltravoxConfig", "AutoModel": "ultravox_model.UltravoxModel", "AutoProcessor": "ultravox_processing.UltravoxProcessor"}, "model_type": "ultravox", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{... | {
"auto_model": "AutoModel",
"custom_class": "ultravox_model.UltravoxModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ar", "be", "bg", "bn", "cs", "cy", "da", "de", "el", "en", "es", "et", "fa", "fi", "fr", "gl", "hi", "hu", "it", "ja", "ka", "lt", "lv", "mk", "mr", "nl", "pl", "pt", "ro", "ru", "sk", "sl", "sr", "sv", "sw", "ta", "th", "tr", "uk", "ur", "vi", ... | # Model Card for Ultravox
Ultravox is a multimodal Speech LLM built around a pretrained [Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) and [whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) backbone.
See https://ultravox.ai for the GitHub repo and more informat... | null | [
"mit"
] | null | [
"ar",
"be",
"bg",
"bn",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"fi",
"fr",
"gl",
"hi",
"hu",
"it",
"ja",
"ka",
"lt",
"lv",
"mk",
"mr",
"nl",
"pl",
"pt",
"ro",
"ru",
"sk",
"sl",
"sr",
"sv",
"sw",
"ta",
"th",
"tr",
"uk",
"ur"... | null | null | [
"bleu"
] | [
"AutoModel",
"UltravoxModel",
"ultravox",
"ultravox_model.UltravoxModel"
] | [
"feature-extraction",
"audio-text-to-text"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
662c2b2b49edec47b04823f4 | 803e3c8528c55bf1 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 352 | tenyx/Llama3-TenyxChat-70B | tenyx | null | 8,398 | 129,816 | False | 2024-04-26T22:31:07Z | 2024-05-08T00:42:32Z | transformers | 64 | 0 | null | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"hexplot_llama3-tenyxchat-70b.png",
"model-00001-of-00030.safetensors",
"model-00002-of-00030.safetensors",
"model-00003-of-00030.safetensors",
"model-00004-of-00030.safetensors",
"model-00005-of-00030.safetensors",
"model-0... | a85d31e3af8fcc847cc9169f1144cf02f5351fab | [
"transformers",
"safetensors",
"llama",
"text-generation",
"tenyx-fine-tuning",
"dpo",
"tenyxchat",
"llama3",
"conversational",
"en",
"dataset:HuggingFaceH4/ultrafeedback_binarized",
"arxiv:2305.18290",
"arxiv:2306.05685",
"license:llama3",
"text-generation-inference",
"endpoints_compa... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["tenyx-fine-tuning", "dp... | # TenyxChat: Language Model Alignment using Tenyx Fine-tuning
Introducing Llama-3-TenyxChat-70B, part of our TenyxChat series trained to function as useful assistants through preference tuning, using Tenyx's advanced fine-tuning technology ([VentureBeat article](https://venturebeat.com/ai/tenyx-aims-to-fix-llms-catast... | null | [
"llama3"
] | [
"HuggingFaceH4/ultrafeedback_binarized"
] | [
"en"
] | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65c5383c469efddc1c3ae440 | 3a732ab237c338af | c21f0239d1cf0f86 | 65,024 | BPE | 64,784 | false | true | false | true | 12 | null | Sequence | ByteLevel | null | [
"Punctuation",
"ByteLevel",
"Digits",
"Split"
] | [
"ByteLevel"
] | 45 | TeeZee/falcon-180B-chat-GPTQ | TeeZee | {
"models": [
{
"_id": "64f5957cab97f9a83ecb71ee",
"id": "tiiuae/falcon-180B-chat"
}
],
"relation": "quantized"
} | 4 | 88,688 | False | 2024-02-08T20:23:24Z | 2024-02-08T22:10:58Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"I32": 177586831360, "F16": 978654208}, "total": 178565485568} | [
".gitattributes",
"ACCEPTABLE_USE_POLICY.txt",
"LICENSE.txt",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00010.safetensors",
"model-00002-of-00010.safetensors",
"model-00003-of-00010.safetensors",
"model-00004-of-00010.safetensors",
"model-00005-of-00010.safetensors",
... | c37cf0b284cc114a8a42eddec66f48ee417ce283 | [
"transformers",
"safetensors",
"falcon",
"text-generation",
"conversational",
"en",
"de",
"es",
"fr",
"dataset:tiiuae/falcon-refinedweb",
"base_model:tiiuae/falcon-180B-chat",
"base_model:quantized:tiiuae/falcon-180B-chat",
"license:unknown",
"text-generation-inference",
"4-bit",
"gptq... | null | {"architectures": ["FalconForCausalLM"], "model_type": "falcon", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"eos_token": "<|endoftext|>", "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "tiiuae/falcon-180B-chat", "datasets": ["tiiuae/falcon-refinedweb"], "eval_results": null, "language": ["en", "de", "es", "fr"], "library_name": null, "license": "unknown", "license_name": null, "license_link": null, "metrics": null, "model_name": "Falcon 180B Chat", "pipeline_tag": null, "tags": null, "... | # Falcon 180B Chat - GPTQ
- Model creator: [Technology Innovation Institute](https://huggingface.co/tiiuae)
- Original model: [Falcon 180B Chat](https://huggingface.co/tiiuae/falcon-180B-chat)
<!-- description start -->
## Description
This repo contains GPTQ model files for [Technology Innovation Institute's Falcon 1... | null | [
"unknown"
] | [
"tiiuae/falcon-refinedweb"
] | [
"en",
"de",
"es",
"fr"
] | 178,565,485,568 | null | null | [
"AutoModelForCausalLM",
"falcon",
"FalconForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6588086008f83845fc2797a0 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | kyujinpy/Sakura-SOLAR-Instruct | kyujinpy | null | 1,482 | 97,250 | False | 2023-12-24T10:30:56Z | 2026-01-11T06:49:44Z | transformers | 28 | 0 | [{"name": "Sakura-SOLAR-Instruct", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 70.99, "name": ... | text-generation | {"parameters": {"F16": 10731524096}, "total": 10731524096} | [
".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",
"sakura.png",
"special_tokens_map.json",
"tokenizer.json",
... | e8a748ac9039957e928ded85ff0efee504fdee6e | [
"transformers",
"safetensors",
"llama",
"text-generation",
"merge",
"conversational",
"en",
"license:cc-by-nc-sa-4.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{% if message['content']%}{{'### System:\n' + message['content']+'\n\n'}}{% endif %}{% elif message['role'] == 'user' %}{{'### User:\... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"language": ["en"], "license": "cc-by-nc-sa-4.0", "pipeline_tag": "text-generation", "tags": ["merge"], "model-index": [{"name": "Sakura-SOLAR-Instruct", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "A... | # **Sakura-SOLAR-Instruct**
<img src='./sakura.png' width=512>
**(주)미디어그룹사람과숲과 (주)마커의 LLM 연구 컨소시엄에서 개발된 모델입니다**
## Model Details
**Model Developers** Kyujin Han (kyujinpy)
**Method**
Using [Mergekit](https://github.com/cg123/mergekit).
I shared the information about my model. (training and code)
**Please ... | null | [
"cc-by-nc-sa-4.0"
] | null | [
"en"
] | 10,731,524,096 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6222b688aac6ea3408d1dba4 | 0a70b8344fad31fe | 5246e34fb40428b7 | 50,257 | BPE | 49,995 | false | true | true | true | 6 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 997 | remotejob/tweetsGPT2fi_v0 | remotejob | null | 24 | 88,671 | False | 2022-03-05T01:02:00Z | 2022-05-27T22:22:53Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"Readme.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"rust_model.ot",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 34abb218bb8e6f61bec9a47c0db81e776229f1a6 | [
"transformers",
"pytorch",
"rust",
"gpt2",
"text-generation",
"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"
} | null | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1802ce | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | sentence-transformers/msmarco-roberta-base-v3 | sentence-transformers | null | 760 | 93,071 | False | 2022-03-02T23:29:05Z | 2025-03-06T13:30:02Z | sentence-transformers | 0 | 0 | null | sentence-similarity | {"parameters": {"I64": 514, "F32": 124645632}, "total": 124646146} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"merges.txt",
"model.safetensors",
"modules.json",
"onnx/model.onnx",
"onnx/model_O1.onnx",
"onnx/model_O2.onnx",
"onnx/model_O3.onnx",
"onnx/model_O4.onnx",
"onnx/model_qint8_arm64.... | c31abad3aeaf98ade999cb879e8b8f9b09255433 | [
"sentence-transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"openvino",
"roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaModel"], "model_type": "roberta", "tokenizer_config": {"unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": t... | {
"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",... | # sentence-transformers/msmarco-roberta-base-v3
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when yo... | null | [
"apache-2.0"
] | null | null | 124,646,146 | null | null | [
"roberta",
"AutoModel",
"RobertaModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
672283c56d880221137b7538 | 9f539b0447a97cc2 | f68b57645b8a1959 | 32,768 | BPE | 61,249 | true | false | true | true | 771 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 964 | UsefulSensors/moonshine-tiny | UsefulSensors | null | 14,350 | 142,256 | False | 2024-10-30T19:06:45Z | 2025-01-30T16:07:38Z | transformers | 27 | 0 | null | automatic-speech-recognition | {"parameters": {"F32": 27092736}, "total": 27092736} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"preprocessor_config.json",
"tokenizer.json"
] | 390624ed33d594443aa4aa221f5b9f283b545b5a | [
"transformers",
"safetensors",
"moonshine",
"automatic-speech-recognition",
"en",
"arxiv:2410.15608",
"arxiv:1810.03993",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MoonshineForConditionalGeneration"], "model_type": "moonshine"} | {
"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": null, "arxiv": "https://arxiv.org/abs/2410.15608"} | # Moonshine
[[Blog]](https://petewarden.com/2024/10/21/introducing-moonshine-the-new-state-of-the-art-for-speech-to-text/) [[Paper]](https://arxiv.org/abs/2410.15608) [[Installation]](https://github.com/usefulsensors/moonshine/blob/main/README.md) [[Podcast]](https://notebooklm.google.com/notebook/d787d6c2-7d7b-478c-b... | null | [
"mit"
] | null | [
"en"
] | 27,092,736 | null | null | [
"AutoModelForSpeechSeq2Seq",
"MoonshineForConditionalGeneration",
"moonshine"
] | [
"automatic-speech-recognition"
] | [
"multimodal"
] | [
"audio"
] | [
"text"
] |
6867bffcc015bfcb8fd15288 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | AI-MO/Kimina-Prover-Distill-1.7B | AI-MO | {
"models": [
{
"_id": "680da7517bcb5198014ad394",
"id": "Qwen/Qwen3-1.7B"
}
],
"relation": "finetune"
} | 684 | 99,402 | False | 2025-07-04T11:50:20Z | 2025-07-10T11:33:21Z | transformers | 7 | 0 | null | text-generation | {"parameters": {"BF16": 2031739904}, "total": 2031739904} | [
".gitattributes",
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"added_tokens.json",
"config.json",
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"merges.txt",
"model.safetensors",
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"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 3d66bc560a29bdee21322eba9b02971a7b891ef5 | [
"transformers",
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"text-generation",
"chat",
"conversational",
"en",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may call o... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-1.7B", "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": ["chat"]} | null | null | [
"apache-2.0"
] | null | [
"en"
] | 2,031,739,904 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68c88388ba74490db616d430 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | lmstudio-community/Qwen3-Next-80B-A3B-Instruct-MLX-4bit | lmstudio-community | {
"models": [
{
"_id": "68c04a8865953b21d7f88ec6",
"id": "Qwen/Qwen3-Next-80B-A3B-Instruct"
}
],
"relation": "quantized"
} | 31,508 | 298,102 | False | 2025-09-15T21:22:16Z | 2025-09-17T17:08:33Z | transformers | 7 | 0 | null | text-generation | {"parameters": {"BF16": 2491172608, "U32": 9965428736}, "total": 79674388992} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00009.safetensors",
"model-00002-of-00009.safetensors",
"model-00003-of-00009.safetensors",
"model-00004-of-00009.safetensors",
"model-00005-of-0000... | 6d14222d4664dba1aa9f3251696c8254c6e994af | [
"transformers",
"safetensors",
"qwen3_next",
"text-generation",
"mlx",
"conversational",
"base_model:Qwen/Qwen3-Next-80B-A3B-Instruct",
"base_model:quantized:Qwen/Qwen3-Next-80B-A3B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"4-bit",
"region:us"
] | null | {"architectures": ["Qwen3NextForCausalLM"], "model_type": "qwen3_next", "quantization_config": {"bits": 4}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].ro... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-Next-80B-A3B-Instruct", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, "p... | ## 💫 Community Model> Qwen3-Next-80B-A3B-Instruct by Qwen
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [Qwen](https://huggingface.co/Qwen)<br>
**O... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct/blob/main/LICENSE"
] | null | null | 79,674,388,992 | null | null | [
"qwen3_next",
"Qwen3NextForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67b5af2b4adadc05e7f7083f | 8f765ac1c479905b | 0bc4a44a6c0c4e50 | 102,400 | Unigram | null | false | true | true | true | 18 | null | Metaspace | Sequence | null | [
"Metaspace"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 533 | sbintuitions/modernbert-ja-310m | sbintuitions | null | 4,524 | 168,873 | False | 2025-02-19T10:15:07Z | 2025-05-01T03:43:10Z | transformers | 21 | 1 | null | fill-mask | {"parameters": {"F32": 315304960}, "total": 315304960} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 77675fc96a7e445e982e2ba90246b816efc74ec6 | [
"transformers",
"safetensors",
"modernbert",
"fill-mask",
"ja",
"en",
"arxiv:2412.13663",
"arxiv:2104.09864",
"arxiv:2404.10830",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ModernBertForMaskedLM"], "model_type": "modernbert", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<cls>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "<sep>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ja", "en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "fill-mask", "tags": null} | # ModernBERT-Ja-310M
This repository provides Japanese ModernBERT trained by [SB Intuitions](https://www.sbintuitions.co.jp/).
[ModernBERT](https://arxiv.org/abs/2412.13663) is a new variant of the BERT model that combines local and global attention, allowing it to handle long sequences while maintaining high computa... | null | [
"mit"
] | null | [
"ja",
"en"
] | 315,304,960 | null | null | [
"ModernBertForMaskedLM",
"modernbert",
"AutoModelForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
649d7f69b815538187a3c96b | 2e331f86ac13f348 | 94b7b509061003bc | 50,259 | BPE | 50,000 | false | true | true | true | 3 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 998 | Writer/palmyra-med-20b | Writer | null | 891 | 92,841 | False | 2023-06-29T12:56:09Z | 2024-08-17T23:49:59Z | transformers | 37 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"pytorch_model-00001-of-00005.bin",
"pytorch_model-00002-of-00005.bin",
"pytorch_model-00003-of-00005.bin",
"pytorch_model-00004-of-00005.bin",
"pytorch_model-00005-of-00005.bin",
"pytorc... | a9ba35209b6dd201bcd807723fe9201bf3545102 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"medical",
"palmyra",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "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": 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": ["medical", "palmyra"]} | **DEPRECATED MODEL NOTICE**
==========================
Please note that this model is no longer maintained or supported by our team. We strongly advise against using it in production or for any critical applications.
Instead, we recommend using our latest and greatest models, which can be found at:
https://huggingfa... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6287b1d8589a0ce871778dbc | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | Davlan/afro-xlmr-large | Davlan | null | 1,512 | 114,025 | False | 2022-05-20T15:20:56Z | 2023-09-11T07:37:38Z | transformers | 12 | 0 | [{"name": "afro-xlmr-large", "results": []}] | fill-mask | {"parameters": {"I64": 514, "F16": 560142482}, "total": 560142996} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | 7036fa1ed38d3418a122d3c7e00d5c748ed29f08 | [
"transformers",
"pytorch",
"jax",
"safetensors",
"xlm-roberta",
"fill-mask",
"generated_from_trainer",
"en",
"fr",
"ar",
"ha",
"ig",
"yo",
"rn",
"rw",
"sn",
"xh",
"zu",
"om",
"am",
"so",
"st",
"ny",
"mg",
"sw",
"af",
"license:mit",
"endpoints_compatible",
"dep... | null | {"architectures": ["XLMRobertaForMaskedLM"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normali... | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": ["en", "fr", "ar", "ha", "ig", "yo", "rn", "rw", "sn", "xh", "zu", "om", "am", "so", "st", "ny", "mg", "sw", "af"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "afro-xlmr-large",... | # afro-xlmr-large
AfroXLMR-large was created by MLM adaptation of XLM-R-large model on 17 African languages (Afrikaans, Amharic, Hausa, Igbo, Malagasy, Chichewa, Oromo, Nigerian-Pidgin, Kinyarwanda, Kirundi, Shona, Somali, Sesotho, Swahili, isiXhosa, Yoruba, and isiZulu) covering the major African language families an... | null | [
"mit"
] | null | [
"en",
"fr",
"ar",
"ha",
"ig",
"yo",
"rn",
"rw",
"sn",
"xh",
"zu",
"om",
"am",
"so",
"st",
"ny",
"mg",
"sw",
"af"
] | 560,142,996 | null | null | [
"AutoModelForMaskedLM",
"xlm-roberta",
"XLMRobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6563e6db2cd8dac568a97129 | f2d221367d3456d4 | a13ef8b251044399 | 69,344 | BPE | 89,205 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 999 | lcw99/zephykor-ko-beta-7b-chang | lcw99 | null | 24 | 88,119 | False | 2023-11-27T00:46:19Z | 2023-12-25T01:17:13Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F16": 7547654144}, "total": 7547654144} | [
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} | {"base_model": null, "datasets": ["jondurbin/airoboros-gpt4-m2.0"], "eval_results": null, "language": null, "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | ### Overview
This is an instruction fine-tuned llama-2 model, using synthetic instructions generated by [airoboros](https://github.com/jondurbin/airoboros)
- The 2.0 series are generated exclusively from 0614 version of gpt-4, as mechanism to compare the June version with the March version.
- The m2.0 series have the... | null | [
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] | 64 | qanastek/XLMRoberta-Alexa-Intents-Classification | qanastek | null | 476 | 89,007 | False | 2022-05-04T22:36:57Z | 2022-05-05T00:52:15Z | transformers | 52 | 0 | null | text-classification | null | [
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* [LABRAK Yanis](https://www.linkedin.com/in/yanis-labrak-8a7412145/) (1)
**Affiliations**
1. [LIA, NLP team](https://lia.univ-avignon.fr/), Avignon University, Avignon, France.
## Demo: How to use in HuggingFace Transformers Pipeline
Requires [transformers](https://pypi.org/project/transformer... | null | [
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] | [
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"ByteLevel"
] | 111 | mmnga/Llama-3-70B-japanese-suzume-vector-v0.1 | mmnga | null | 8,352 | 128,719 | False | 2024-04-28T04:11:49Z | 2024-04-28T07:46:32Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
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<!-- Provide a quick summary of what the model is/does. -->
*実験モデルです / This is an experimental model.*
[lightblue/suzume-llama-3-8B-japanese](https://huggingface.co/lightblue/suzume-llama-3-8B-japanese)と、
[meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3... | null | [
"llama3"
] | null | [
"ja",
"en"
] | 70,553,706,496 | null | null | [
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"text"
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 715 | Locutusque/Hercules-2.5-Mistral-7B | Locutusque | {
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{
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"id": "mistralai/Mistral-7B-v0.1"
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],
"relation": "finetune"
} | 30 | 87,645 | False | 2024-02-10T08:23:41Z | 2024-02-12T16:59:28Z | transformers | 7 | 0 | [{"name": "Hercules-2.5-Mistral-7B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 62.03, "name"... | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
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65e1ec83ef53e227b3b0ca95 | 83bf28f8b6767a2f | ae88e903e2b563a1 | 50,295 | BPE | 50,000 | false | true | true | true | 39 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 85 | abacaj/phi-2-super | abacaj | null | 138 | 87,903 | False | 2024-03-01T14:56:03Z | 2024-03-02T15:45:40Z | transformers | 84 | 0 | [{"name": "phi-2-super", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "Instruction Following Eval", "type": "wis-k/instruction-following-eval"}, "metrics": [{"type": "acc", "name": "prompt_level_loose_acc", "value": 0.2717, "verified": false}], "source": {"name": "Lig... | text-generation | {"parameters": {"BF16": 2779683840}, "total": 2779683840} | [
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"phi",
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"convAI",
"conversational",
"custom_code",
"en",
"license:mit",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["PhiForCausalLM"], "auto_map": {"AutoConfig": "microsoft/phi-2--configuration_phi.PhiConfig", "AutoModelForCausalLM": "microsoft/phi-2--modeling_phi.PhiForCausalLM"}, "model_type": "phi", "tokenizer_config": {"bos_token": "<|endoftext|>", "chat_template": "{{ bos_token }}{% for message in messages %}... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"language": ["en"], "license": "mit", "license_link": "https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE", "pipeline_tag": "text-generation", "tags": ["convAI", "conversational"], "widget": [{"text": "Hello who are you?", "example_title": "Identity"}, {"text": "What can you do?", "example_title": "Capabiliti... | # Phi-2-super (SFT + cDPO)
Base Model: [microsoft/phi-2](https://huggingface.co/microsoft/phi-2)
# How to run inference:
```python
import transformers
import torch
if __name__ == "__main__":
mod... | null | [
"mit",
"https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE"
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"en"
] | 2,779,683,840 | null | null | [
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6790cea98fba8774488894ad | 5b8a6156b5b6e013 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 37 | billatsectorflow/stella_en_400M_v5 | billatsectorflow | null | 1,517 | 107,613 | False | 2025-01-22T10:55:37Z | 2025-01-22T11:45:51Z | sentence-transformers | 3 | 0 | [{"name": "stella_en_400M_v5", "results": [{"dataset": {"config": "en", "name": "MTEB AmazonCounterfactualClassification (en)", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205", "split": "test", "type": "mteb/amazon_counterfactual"}, "metrics": [{"type": "accuracy", "value": 92.35820895522387, "verified": false},... | sentence-similarity | {"parameters": {"F32": 435188736}, "total": 435188736} | [
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"auto_model": "AutoModel",
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} | {"license": "mit", "tags": ["mteb", "sentence-transformers", "transformers", "sentence-similarity"], "model-index": [{"name": "stella_en_400M_v5", "results": [{"task": {"type": "Classification"}, "dataset": {"name": "MTEB AmazonCounterfactualClassification (en)", "type": "mteb/amazon_counterfactual", "config": "en", "s... | # Updates
Hi, everyone, thanks for using stella models.
After six months of work, I trained the jasper model on top of the stella model, which is a multimodal model, and it can be ranked 2 in mteb (submitted the results on 2024-12-11, which may need official review https://github.com/embeddings-benchmark/results/pull/... | null | [
"mit"
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"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
66b183c9920204efc2ed95e1 | 539b24ec3c9dbddd | 6ce596b7c0f62c6d | 151,647 | BPE | 151,387 | true | true | true | true | 4 | NFC | Sequence | ByteLevel | [
"NFC"
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"Split",
"ByteLevel"
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] | 234 | lmms-lab/llava-onevision-qwen2-72b-ov-sft | lmms-lab | null | 202 | 89,574 | False | 2024-08-06T02:00:41Z | 2024-09-02T07:25:33Z | transformers | 15 | 0 | null | text-generation | {"parameters": {"BF16": 73180522016}, "total": 73180522016} | [
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"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": ["lmms-lab/LLaVA-OneVision-Data"], "eval_results": null, "language": ["en", "zh"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["multimodal"]} | # 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. [License... | null | [
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"gpt_neo",
"AutoModelForCausalLM",
"GPTNeoForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
664f66f3618c64fe01779ff1 | 21a9a365f9765414 | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 454 | unsloth/Phi-3-medium-4k-instruct-bnb-4bit | unsloth | null | 1,444 | 92,081 | False | 2024-05-23T15:55:31Z | 2025-06-15T02:58:36Z | transformers | 7 | 0 | null | text-generation | {"parameters": {"F32": 908160, "BF16": 328750080, "U8": 14057568510}, "total": 14387226750} | [
".gitattributes",
"README.md",
"added_tokens.json",
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"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokeniz... | 7e542c8531bb16bca41ebfc9776e21168cfe2cf8 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"unsloth",
"phi3",
"phi",
"conversational",
"en",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"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": "<|endoftext|>", "pad_token": "<|placeholder6|>", "unk_token": "<unk>", "use_default_system_promp... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "phi3", "transformers", "phi"]} | # 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 Phi-3 Medium here: https://colab.research.google.com/drive/1hhdhBa1j_hsymiW9m-WzxQtgqTH_NHqi?usp=sharing
We have a Google Colab Tesla T4 noteb... | null | [
"mit"
] | null | [
"en"
] | 14,387,226,750 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63c4b565bfd39d7373a87c30 | a3747d9d02eeadba | 36650505ce1aaef9 | 30,000 | Unigram | null | true | true | true | true | 6 | Sequence | Metaspace | Metaspace | [
"Replace",
"Replace",
"Lowercase",
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 1,001 | bongsoo/albert-small-kor-cross-encoder-v1 | bongsoo | null | 535 | 88,130 | False | 2023-01-16T02:24:37Z | 2023-01-30T02:32:27Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | 54d83edd7218ee9d9d12c1ebcba6756be79a2d79 | [
"transformers",
"pytorch",
"albert",
"text-classification",
"ko",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["AlbertForSequenceClassification"], "model_type": "albert", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": {"__type": "AddedToken", "content": "[MASK]", "lstrip": true, "normalized": true, "rstrip": false, "single_word": false}, "pad_token": "[PAD... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ko"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # albert-small-kor-cross-encoder-v1
- albert-small-kor-v1 모델을 훈련시켜 cross-encoder로 파인튜닝한 모델
- This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.
# Training
- sts(10)-nli(3)-sts(10)-nli(3)-sts(10) 훈련 시킴 (**d... | null | [
"apache-2.0"
] | null | [
"ko"
] | null | null | null | [
"AlbertForSequenceClassification",
"albert",
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"text"
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"logits"
] |
654c201947053d20c788cd4d | 013a2a604d117f5d | ea059d203298896f | 46,336 | BPE | 77,738 | true | false | true | true | 8 | Sequence | null | Sequence | [
"NFKC",
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"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 564 | Kaeri-Jenti/llama-2-koen-13b-v1.2 | Kaeri-Jenti | null | 9 | 87,115 | False | 2023-11-08T23:56:09Z | 2023-11-09T00:59:04Z | transformers | 0 | 0 | null | text-generation | null | [
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | null | [
"llama2"
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 133 | TheBloke/guanaco-7B-HF | TheBloke | null | 1,473 | 99,695 | False | 2023-05-25T20:17:10Z | 2023-06-05T00:10:27Z | transformers | 13 | 0 | null | text-generation | null | [
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"text-generation",
"license:other",
"text-generation-inference",
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
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<div style="width: 100%;">
<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%;">
<div style="display: flex; flex-direction: column; a... | null | [
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"text"
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6740b8481362439725ef2a3e | b73645feff7a5171 | ba4ae0f1b0a053ec | 49,155 | BPE | 48,900 | false | true | false | true | 20 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 347 | HuggingFaceTB/SmolVLM-Base | HuggingFaceTB | {
"models": [
{
"_id": "6723892e4a49116d8ead173e",
"id": "HuggingFaceTB/SmolLM2-1.7B-Instruct"
}
],
"relation": "finetune"
} | 1,421 | 97,659 | False | 2024-11-22T16:58:48Z | 2024-11-28T16:22:07Z | transformers | 86 | 0 | null | image-text-to-text | {"parameters": {"BF16": 2246272880}, "total": 2246272880} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.json",
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"merges.txt",
"model.safetensors",
"preprocessor_config.json",
"processor_config.json",
"special_tokens_map.json",
"tokenizer.json",
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] | a576ab7b4354916a0cb5b58a3bd973a9a526ee7c | [
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"base_model:finetune:HuggingFaceTB/SmolLM2-1.7B-Instruct",
"license:apache-2.0",
"e... | null | {"architectures": ["Idefics3ForConditionalGeneration"], "model_type": "idefics3", "processor_config": {"chat_template": "<|im_start|>{% for message in messages %}{{message['role'].capitalize()}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}{% if... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["HuggingFaceTB/SmolLM2-1.7B-Instruct", "google/siglip-so400m-patch14-384"], "datasets": ["HuggingFaceM4/the_cauldron", "HuggingFaceM4/Docmatix"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null... | <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/SmolVLM.png" width="800" height="auto" alt="Image description">
# SmolVLM
SmolVLM is a compact open multimodal model that accepts arbitrary sequences of image and text inputs to produce text outputs.
Designed for efficiency, SmolV... | null | [
"apache-2.0"
] | [
"HuggingFaceM4/the_cauldron",
"HuggingFaceM4/Docmatix"
] | [
"en"
] | 2,246,272,880 | null | null | [
"AutoModelForImageTextToText",
"Idefics3ForConditionalGeneration",
"idefics3"
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"image-text-to-text"
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"multimodal"
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"text",
"image"
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"text"
] |
621ffdc136468d709f17bab5 | 382b5a4eb98f0296 | d965e4a9140ecf72 | 21,128 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 33 | hfl/chinese-pert-base | hfl | null | 189 | 87,398 | False | 2022-03-02T23:29:05Z | 2022-02-24T02:57:09Z | transformers | 13 | 0 | null | feature-extraction | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
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] | 54f84f9b553c9184d92e1d476010299aac42cf86 | [
"transformers",
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"tf",
"bert",
"feature-extraction",
"zh",
"license:cc-by-nc-sa-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModel",
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"pipeline_tag": "feature-extraction",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": "cc-by-nc-sa-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Please use 'Bert' related functions to load this model!
Under construction...
Please visit our GitHub repo for more information: https://github.com/ymcui/PERT | null | [
"cc-by-nc-sa-4.0"
] | null | [
"zh"
] | null | null | null | [
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"embeddings"
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"BertNormalizer"
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] | 37 | elozano/bert-base-cased-news-category | elozano | null | 60 | 93,148 | False | 2022-03-02T23:29:05Z | 2022-03-01T20:30:48Z | transformers | 10 | 0 | null | text-classification | null | [
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] | fbdaa11402acf946b10c8ed24fe87017b1f6b726 | [
"transformers",
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"bert",
"text-classification",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
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] | [
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] | [
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] | [
"logits"
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6622a749ef00d8ae7a8ce793 | 3f287b04362fff24 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 158 | migtissera/Tess-2.0-Llama-3-70B | migtissera | null | 8,418 | 127,899 | False | 2024-04-19T17:18:01Z | 2024-06-02T01:04:52Z | transformers | 11 | 0 | null | text-generation | {"parameters": {"F16": 70553706496}, "total": 70553706496} | [
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"config.json",
"generation_config.json",
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"license:llama3",
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|s... | {
"auto_model": "AutoModelForCausalLM",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | 
# Tess-2.0-Llama-3-70B
Tess, short for Tesoro (Treasure in Italian), is a general purpose Large Language Model series. Tess-2.0-Llama-3-70B was trained on the meta-llama/Meta-Llama-3-70B base.
Compute for Tess-2.0-Llama-3-70B ... | null | [
"llama3"
] | null | null | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65104786c945dfc938a7031f | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | 42MARU/GenAI-llama-2-13b | 42MARU | null | 12 | 86,924 | False | 2023-09-24T14:28:22Z | 2023-11-18T04:34:33Z | transformers | 5 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"meta-license/LICENSE.txt",
"meta-license/Responsible-Use-Guide.pdf",
"meta-license/USE_POLICY.md",
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"pytorch_model-00002-of-00003.bin",
"pytorch_model-00003-of-00003.bin",
"pytorch_model.b... | 99440b6258a703839669aa6d0d5528632d4ddd78 | [
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"llama-2",
"instruct",
"instruction",
"en",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": false, "rstrip... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": 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": ["llama-2", "instruct", "instruction"]} | # GenAI-llama-2-13b
### Model Details
- Developed by: [42MARU](https://www.42maru.ai/en/)
- Backbone Model: [LLaMA-2](https://github.com/facebookresearch/llama/tree/main)
- Library: [transformers](https://github.com/huggingface/transformers)
### Used Datasets
- Orca-style dataset
- Platypus
### Prompt Template
```
#... | null | null | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1794e0 | eb52febf08b1f46a | 046224ca498cefbf | 64,000 | WordPiece | null | true | true | true | true | 36 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 323 | aubmindlab/bert-large-arabertv2 | aubmindlab | null | 1,219 | 93,813 | False | 2022-03-02T23:29:05Z | 2023-03-20T13:07:11Z | transformers | 12 | 0 | null | fill-mask | {"parameters": {"I64": 512, "F32": 370541058}, "total": 370541570} | [
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"runs/events.out.tfevents.1606705402.tpu-mother",
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"tensorboard",
"safetensors",
"bert",
"fill-mask",
"ar",
"arxiv:2003.00104",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "ar", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": " \u0639\u0627\u0635\u0645 +\u0629 \u0644\u0628\u0646\u0627\u0646... | # AraBERT v1 & v2 : Pre-training BERT for Arabic Language Understanding
<img src="https://raw.githubusercontent.com/aub-mind/arabert/master/arabert_logo.png" width="100" align="left"/>
**AraBERT** is an Arabic pretrained language model based on [Google's BERT architechture](https://github.com/google-research/bert). A... | null | null | null | [
"ar"
] | 370,541,570 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
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"logits"
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621ffdc136468d709f1794da | 209ee53ab6125c5c | b176581335942aae | 64,000 | WordPiece | null | true | true | true | true | 8 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 1,002 | aubmindlab/bert-base-arabertv01 | aubmindlab | null | 41 | 87,270 | False | 2022-03-02T23:29:05Z | 2023-06-09T12:24:20Z | transformers | 3 | 0 | null | fill-mask | {"parameters": {"F32": 135851010}, "total": 135851010} | [
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"config.json",
"flax_model.msgpack",
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"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 01f6b7d2d17afcd0f79498f26f47dfc6207b56ea | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"ar",
"dataset:wikipedia",
"dataset:OSIAN",
"dataset:1.5B_Arabic_Corpus",
"arxiv:2003.00104",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["wikipedia", "OSIAN", "1.5B_Arabic_Corpus"], "eval_results": null, "language": "ar", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": " \u0639\u0627\u0635\u064... | # !!! A newer version of this model is available !!! [AraBERTv02](https://huggingface.co/aubmindlab/bert-base-arabertv02)
# AraBERT v1 & v2 : Pre-training BERT for Arabic Language Understanding
<img src="https://raw.githubusercontent.com/aub-mind/arabert/master/arabert_logo.png" width="100" align="left"/>
**AraBERT... | null | null | [
"wikipedia",
"OSIAN",
"1.5B_Arabic_Corpus"
] | [
"ar"
] | 135,851,010 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
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62bcc2bad2c8a6542f4a5491 | 5afd7d59d2aa5e01 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
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"BertPreTokenizer"
] | [
"WordPiece"
] | 125 | austinmw/distilbert-base-uncased-finetuned-tweets-sentiment | austinmw | null | 12 | 86,695 | False | 2022-06-29T21:23:06Z | 2022-06-29T22:18:47Z | transformers | 2 | 0 | [{"name": "distilbert-base-uncased-finetuned-tweets-sentiment", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "tweet_eval", "type": "tweet_eval", "args": "sentiment"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value": 0.7295, "verified": false}, {"n... | text-classification | null | [
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} | {"datasets": ["tweet_eval"], "license": "apache-2.0", "metrics": ["accuracy", "f1"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-tweets-sentiment", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tweet_eval", "... | <!-- 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. -->
# distilbert-base-uncased-finetuned-tweets-sentiment
This model is a fine-tuned version of [distilbert-base-uncased](https://huggin... | null | [
"apache-2.0"
] | [
"tweet_eval"
] | null | null | null | [
"accuracy",
"f1"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6680570c2b1f40e838b2eaad | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 106 | UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2 | UCLA-AGI | null | 1,372 | 92,614 | False | 2024-06-29T18:48:44Z | 2024-07-01T23:46:19Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"BF16": 9241705984}, "total": 9241705984} | [
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"model.safetensors.index.json",
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"... | b7590721d92bf6e0606e3dbc1ca2c229b7c534b4 | [
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"arxiv:2405.00675",
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"endpoints_compatible",
"deploy:azure",
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] | null | {"architectures": ["Gemma2ForCausalLM"], "model_type": "gemma2", "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["openbmb/UltraFeedback"], "eval_results": null, "language": ["en"], "library_name": null, "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | Self-Play Preference Optimization for Language Model Alignment (https://arxiv.org/abs/2405.00675)
# Gemma-2-9B-It-SPPO-Iter2
This model was developed using [Self-Play Preference Optimization](https://arxiv.org/abs/2405.00675) at iteration 2, based on the [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b... | null | [
"gemma"
] | [
"openbmb/UltraFeedback"
] | [
"en"
] | 9,241,705,984 | null | null | [
"AutoModelForCausalLM",
"gemma2",
"Gemma2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6431c8fc6758730899da168e | 98e5292f74970347 | 3223918073c8709d | 50,260 | BPE | 50,000 | false | true | true | true | 4 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 772 | vicgalle/gpt2-alpaca-gpt4 | vicgalle | null | 1,028 | 91,161 | False | 2023-04-08T20:05:16Z | 2023-11-30T10:37:59Z | transformers | 25 | 0 | null | text-generation | {"parameters": {"F32": 124442112, "U8": 12582912}, "total": 137025024} | [
".gitattributes",
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"onnx/config.json",
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"onnx/decoder_model_merged.onnx",
"onnx/decoder_with_past_model.onnx",
"onnx/generation_config.json",
"onnx/merges.tx... | f23966a222c377fe5635293185f83df6504353ff | [
"transformers",
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"gpt2",
"text-generation",
"instruction-tuning",
"alpaca",
"gpt4",
"en",
"dataset:vicgalle/alpaca-gpt4",
"doi:10.57967/hf/1408",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "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": ["vicgalle/alpaca-gpt4"], "eval_results": null, "language": ["en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["instruction-tuning", "alpaca", "gpt4"]} | # GPT-2 finetuned with Alpaca-GPT4
### Examples
The following samples were generated with `{"temperature" : 0.7, "top_p" : 0.92, "top_k" : 0}`:
##### **Give three tips for a good meal**
```
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
... | null | [
"mit"
] | [
"vicgalle/alpaca-gpt4"
] | [
"en"
] | 137,025,024 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
664a27162b528039ed2d929f | a7b0a99838360123 | cad4902422b140fb | 64,000 | BPE | 110,029 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 933 | Azure99/blossom-v5.1-34b | Azure99 | null | 8,374 | 127,697 | False | 2024-05-19T16:21:42Z | 2024-07-24T07:36:48Z | transformers | 5 | 0 | null | text-generation | {"parameters": {"BF16": 34388917248}, "total": 34388917248} | [
".gitattributes",
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"model-00006-of-00007.safetensors",
"model-0... | d43283c52d7df164e1d3542745e9d505d6269042 | [
"transformers",
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"llama",
"text-generation",
"conversational",
"zh",
"en",
"dataset:Azure99/blossom-chat-v3",
"dataset:Azure99/blossom-math-v4",
"dataset:Azure99/blossom-wizard-v3",
"dataset:Azure99/blossom-orca-v3",
"license:apache-2.0",
"text-generation-inference",
"endpoin... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|startoftext|>", "chat_template": "A chat between a human and an artificial intelligence bot. The bot gives helpful, detailed, and polite answers to the human's questions.\n{% for message in messages %}{% set content = me... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Azure99/blossom-chat-v3", "Azure99/blossom-math-v4", "Azure99/blossom-wizard-v3", "Azure99/blossom-orca-v3"], "eval_results": null, "language": ["zh", "en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null,... | # **BLOSSOM-v5.1-34b**
[💻Github](https://github.com/Azure99/BlossomLM) • [🚀Blossom Chat Demo](https://blossom-chat.com/)
### Introduction
Blossom is a conversational large language model, fine-tuned on the Blossom Orca/Wizard/Chat/Math mixed dataset based on the Yi-1.5-34B pre-trained model. Blossom possesses robu... | null | [
"apache-2.0"
] | [
"Azure99/blossom-chat-v3",
"Azure99/blossom-math-v4",
"Azure99/blossom-wizard-v3",
"Azure99/blossom-orca-v3"
] | [
"zh",
"en"
] | 34,388,917,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68e5484b5e3667b1f21de5ca | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | nvidia/llama-embed-nemotron-8b | nvidia | null | 42,218 | 720,064 | False | 2025-10-07T17:05:15Z | 2026-01-12T08:30:38Z | sentence-transformers | 149 | 3 | null | feature-extraction | null | [
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"model-00004-of-00004... | 1acaf42b890bafa464ef9a58d1c0db0dd26120d4 | [
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"arxiv:2502.13595",
"license:other",
"text-embed... | null | {"architectures": ["LlamaBidirectionalModel"], "auto_map": {"AutoConfig": "llama_bidirectional_model.LlamaBidirectionalConfig", "AutoModel": "llama_bidirectional_model.LlamaBidirectionalModel"}, "model_type": "llama_bidirec", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|end_of_text|>", "pad_to... | {
"auto_model": "AutoModel",
"custom_class": "llama_bidirectional_model.LlamaBidirectionalModel",
"pipeline_tag": "feature-extraction",
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} | {"base_model": null, "datasets": ["nvidia/embed-nemotron-dataset-v1"], "eval_results": null, "language": ["multilingual"], "library_name": "sentence-transformers", "license": "other", "license_name": "customized-nscl-v1", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["tr... | null | null | [
"other",
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"AutoModel",
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67ede10c8f7432ed6feb662a | 191e06b04083279c | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
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"BertPreTokenizer"
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"WordPiece"
] | 26 | GozdeA/finetuned-bertweet-poskd3 | GozdeA | null | 1,235 | 111,441 | False | 2025-04-03T01:14:52Z | 2025-04-03T01:15:04Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"F32": 66375953}, "total": 66375953} | [
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"transformers",
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"distilbert",
"token-classification",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"auto_model": "AutoModelForTokenClassification",
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"AutoModelForTokenClassification",
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655b33f85f93aee96e03909f | 98643f76e6c2d3e0 | 291a9305acaae14c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 1,003 | medkit/DrBERT-CASM2 | medkit | null | 1,264 | 101,644 | False | 2023-11-20T10:24:56Z | 2023-11-20T10:24:56Z | transformers | 4 | 0 | null | token-classification | {"parameters": {"I64": 512, "F32": 108897031}, "total": 108897543} | [
".gitattributes",
"README.md",
"config.json",
"history.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"trainer_config.yml",
"vocab.txt"
] | e5844c7cbc277e92ba53828bb4eb388c64d49976 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"medical",
"biomedical",
"medkit-lib",
"fr",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"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": ["fr"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": ["seqeval"], "model_name": null, "pipeline_tag": "token-classification", "tags": ["medical", "biomedical", "medkit-lib"], "widget": [{... | # DrBERT-CASM2
## Model description
**DrBERT-CASM2** is a French Named Entity Recognition model that was fine-tuned from
[DrBERT](https://huggingface.co/Dr-BERT/DrBERT-4GB-CP-PubMedBERT): A PreTrained model in French for biomedical and clinical domains.
It has been trained to detect the following type of entities:... | null | [
"mit"
] | null | [
"fr"
] | 108,897,543 | null | [
"seqeval"
] | [
"AutoModelForTokenClassification",
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"bert"
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"text"
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621ffdc136468d709f1798b7 | 2f7eea950a857bd6 | 05fbed0d16189db4 | 50,135 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 1,004 | beomi/beep-KcELECTRA-base-hate | beomi | null | 126 | 87,013 | False | 2022-03-02T23:29:05Z | 2021-10-23T05:48:36Z | transformers | 2 | 0 | null | text-classification | null | [
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"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 41220dd1598bb646f6ca87e80a4229f5b6d1014c | [
"transformers",
"pytorch",
"electra",
"text-classification",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ElectraForSequenceClassification"], "model_type": "electra", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"ElectraForSequenceClassification",
"AutoModelForSequenceClassification",
"electra"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65a77a47f913d5e9b6afd55a | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | lightblue/karasu-1.1B | lightblue | null | 3,522 | 93,796 | False | 2024-01-17T06:57:11Z | 2024-02-03T13:35:52Z | transformers | 7 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 257a7e002a62913b606695bd20ee3e044f97cf11 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"ja",
"dataset:oscar-corpus/OSCAR-2301",
"dataset:mc4",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["oscar-corpus/OSCAR-2301", "mc4"], "eval_results": null, "language": ["ja"], "library_name": null, "license": "apache-2.0", "license_name": "tongyi-qianwen-license-agreement", "license_link": "https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT", "metrics": ... | <p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64c8a2e01c25d2c581a381c1/9CbN4lDGU42c-7DmK_mGM.png" alt="drawing" width="600"/>
</p>
TinyLlama + Japanese pre-training (50,004 steps)
# How to use
### Hugggingface
```python
from transformers import AutoTokenizer, AutoModelForCausa... | null | [
"apache-2.0",
"tongyi-qianwen-license-agreement",
"https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT"
] | [
"oscar-corpus/OSCAR-2301",
"mc4"
] | [
"ja"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1803f1 | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | shahrukhx01/roberta-base-boolq | shahrukhx01 | null | 17 | 86,437 | False | 2022-03-02T23:29:05Z | 2023-04-05T07:05:46Z | transformers | 2 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 124647170}, "total": 124647684} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | f9678b016db3954525162c97d9e59adb79115f25 | [
"transformers",
"pytorch",
"safetensors",
"roberta",
"text-classification",
"boolean-qa",
"en",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": 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": ["boolean-qa"], "widget": [{"text": "Is Berlin the smallest city of Germany? <s> Berlin is... | # Labels Map
LABEL_0 => **"NO"** <br/>
LABEL_1 => **"YES"**
```python
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
)
model = AutoModelForSequenceClassification.from_pretrained("shahrukhx01/roberta-base-boolq")
model.to(device)
#model.push_to_hub("roberta-base-boolq")
tokeni... | null | null | null | [
"en"
] | 124,647,684 | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64cd73904dfd5df707dccb4d | 2012b52fa41ec860 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 113 | lgaalves/gpt2-dolly | lgaalves | null | 1,282 | 101,463 | False | 2023-08-04T21:54:24Z | 2023-11-17T22:43:29Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"F16": 124439808}, "total": 124439808} | [
".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"
] | 268164679a9ba2065fddbaa8fb594583def16ba1 | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"en",
"dataset:databricks/databricks-dolly-15k",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "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": ["databricks/databricks-dolly-15k"], "eval_results": null, "language": ["en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | # GPT-2-dolly
**GPT-2-dolly** is an instruction fine-tuned model based on the GPT-2 transformer architecture.
### Benchmark Metrics
| Metric | GPT-2-dolly | GPT-2 (base) |
|-----------------------|-------|-------|
| Avg. | **30.91** | 29.99 |
| ARC (25-shot) | **22.70** | 21.... | null | [
"mit"
] | [
"databricks/databricks-dolly-15k"
] | [
"en"
] | 124,439,808 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65ba832fe4b874edb5220cb3 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | marcmendez-aily/BertMeshTerms | marcmendez-aily | null | 28,726 | 188,598 | False | 2024-01-31T17:28:15Z | 2024-02-01T11:01:03Z | transformers | 0 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"config.py",
"handler.py",
"model.py",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 30592eb9bde768159a8db4284f297ee1408be4d4 | [
"transformers",
"pytorch",
"bert",
"custom_code",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["AutoModel"], "auto_map": {"AutoConfig": "config.BertMeshConfig", "AutoModel": "model.BertMeshModel"}, "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": null,
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModel",
"bert"
] | [
null
] | null | null | null |
66e97b50eb534e2d2b48a991 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-3B-Instruct-GPTQ-Int4 | Qwen | {
"models": [
{
"_id": "66e98d74d4219fc3f1db215f",
"id": "Qwen/Qwen2.5-3B-Instruct"
}
],
"relation": "quantized"
} | 3,654 | 111,863 | False | 2024-09-17T12:51:28Z | 2024-10-09T12:27:30Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"I32": 2774532096, "F16": 311406592}, "total": 3085938688} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 68c4276063d1496cdf13d0b8e8221f899bfa77f7 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-3B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"gptq",
... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-3B-Instruct", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "other", "license_name": "qwen-research", "license_link": "https://huggingface.co/Qwen/Qwen2.5-3B-Instruct-GPTQ-Int4/blob/main/LICENSE", "metrics": null, "model_name": null, ... | # Qwen2.5-3B-Instruct-GPTQ-Int4
## Introduction
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
- Significantly *... | null | [
"other",
"qwen-research",
"https://huggingface.co/Qwen/Qwen2.5-3B-Instruct-GPTQ-Int4/blob/main/LICENSE"
] | null | [
"en"
] | 3,085,938,688 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f177a25 | db10cbe7f986673b | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 986 | Unbabel/gec-t5_small | Unbabel | null | 3,821 | 92,382 | False | 2022-03-02T23:29:05Z | 2021-09-27T11:27:48Z | transformers | 26 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | c958d53bfbce19c87342b69fc6bcaba7303d076f | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"grammatical error correction",
"text2text",
"en",
"dataset:clang-8",
"dataset:conll-14",
"dataset:conll-13",
"arxiv:2106.03830",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:... | 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": ["clang-8", "conll-14", "conll-13"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["f0.5"], "model_name": null, "pipeline_tag": null, "tags": ["grammatical error correction", "text2text", ... | This model is an implementation of the paper [A Simple Recipe for Multilingual Grammatical Error Correction](https://arxiv.org/pdf/2106.03830.pdf) from Google where they report the State of the art score in the task of Grammatical Error Correction (GEC).
We implement the version with the T5-small with the reported F_0.... | null | [
"apache-2.0"
] | [
"clang-8",
"conll-14",
"conll-13"
] | [
"en"
] | null | null | [
"f0.5"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
667366a45a2cb9e9609ffb10 | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | haoranxu/Llama-3-Instruct-8B-CPO-SimPO | haoranxu | null | 8,372 | 127,141 | False | 2024-06-19T23:15:48Z | 2024-06-20T18:04:37Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F32": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00007.safetensors",
"model-00002-of-00007.safetensors",
"model-00003-of-00007.safetensors",
"model-00004-of-00007.safetensors",
"model-00005-of-00007.safetensors",
"model-00006-of-00007.safetensors",
"model-0... | 3ca4b5c3a6395ff090e1039d55ac1f6120777302 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2401.08417",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | This repository contains the model release for the joint use of [CPO](https://arxiv.org/abs/2401.08417) and [SimPO](https://github.com/princeton-nlp/SimPO) (CPO-SimPO), please find more details in our [github](https://github.com/fe1ixxu/CPO_SIMPO)! | null | [
"mit"
] | null | null | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
647dae49f14eafc3b4492ce6 | 218e5e4ca5ddf115 | ad4b234fa1a3ca7b | 31,102 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 1,005 | aari1995/German_Sentiment | aari1995 | null | 46 | 86,878 | False | 2023-06-05T09:43:37Z | 2023-06-23T06:29:57Z | transformers | 5 | 0 | null | text-classification | {"parameters": {"I64": 512, "F32": 335738883}, "total": 335739395} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 8910abb50a53924d30832d2349d03cd71ce3b555 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"deepset/gbert-large",
"de",
"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": ["de"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["deepset/gbert-large"]} | # German Sentiment Analysis
This model predicts sentiment for German text.
# Usage
First set up the model:
```python
# if necessary:
# !pip install transformers
from transformers import pipeline
sentiment_model = pipeline(model="aari1995/German_Sentiment")
```
to use it:
```python
sentence = ["Ich liebe die Bahn... | null | null | null | [
"de"
] | 335,739,395 | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66ecec782669c53cec9311f1 | 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-AWQ | Qwen | {
"models": [
{
"_id": "66eaa05b64583d8d2f729e83",
"id": "Qwen/Qwen2.5-Coder-1.5B-Instruct"
}
],
"relation": "quantized"
} | 130,938 | 724,158 | False | 2024-09-20T03:31:04Z | 2024-11-18T12:53:27Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"I32": 1310195712, "F16": 466892288}, "total": 1777088000} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 867d050da8a1af36b04fde627402656b3f918511 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"code",
"codeqwen",
"chat",
"qwen",
"qwen-coder",
"conversational",
"en",
"arxiv:2409.12186",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-Coder-1.5B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-Coder-1.5B-Instruct",
"license:... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen2.5-Coder-1.5B-Instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null... | # Qwen2.5-Coder-1.5B-Instruct-AWQ
## Introduction
Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct/blob/main/LICENSE"
] | null | [
"en"
] | 1,777,088,000 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6573c7c4597698af2ddafd2e | 84892a81d307796d | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 133 | AdaptLLM/medicine-chat | AdaptLLM | null | 909 | 90,833 | False | 2023-12-09T01:49:56Z | 2024-12-02T06:27:53Z | transformers | 54 | 0 | [{"name": "medicine-chat", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 53.75, "name": "normali... | text-generation | {"parameters": {"F32": 6738425856}, "total": 6738425856} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
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"pytorch_model-00002-of-00003.bin",
"pytorch_mod... | 0e6308a9eb7d07cb0b38693987af127fb47577a4 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"biology",
"medical",
"en",
"dataset:EleutherAI/pile",
"dataset:Open-Orca/OpenOrca",
"dataset:GAIR/lima",
"dataset:WizardLM/WizardLM_evol_instruct_V2_196k",
"arxiv:2309.09530",
"arxiv:2411.19930",
"arxiv:2406.14491",
... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["EleutherAI/pile", "Open-Orca/OpenOrca", "GAIR/lima", "WizardLM/WizardLM_evol_instruct_V2_196k"], "language": ["en"], "license": "llama2", "metrics": ["accuracy"], "pipeline_tag": "text-generation", "tags": ["biology", "medical"], "model-index": [{"name": "medicine-chat", "results": [{"task": {"type": "te... | # Adapting LLMs to Domains via Continual Pre-Training (ICLR 2024)
This repo contains the domain-specific chat model developed from **LLaMA-2-Chat-7B**, using the method in our paper [Adapting Large Language Models via Reading Comprehension](https://huggingface.co/papers/2309.09530).
We explore **continued pre-training... | null | [
"llama2"
] | [
"EleutherAI/pile",
"Open-Orca/OpenOrca",
"GAIR/lima",
"WizardLM/WizardLM_evol_instruct_V2_196k"
] | [
"en"
] | 6,738,425,856 | null | [
"accuracy"
] | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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647a672244b6a3ae9d256778 | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | Waterhorse/chessgpt-base-v1 | Waterhorse | null | 1,254 | 89,181 | False | 2023-06-02T22:03:14Z | 2023-07-06T06:19:40Z | transformers | 7 | 0 | null | text-generation | null | [
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"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | e498922d792f3fd7c07471a498ad0a79e0f0b0a0 | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"en",
"dataset:Waterhorse/chess_data",
"arxiv:2306.09200",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 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": ["Waterhorse/chess_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} | # Chessgpt-Base-3B-v1
Chessgpt-Base-v1 is the base model of Chessgpt.
- Base Model: [Chessgpt-base-v1](https://huggingface.co/Waterhorse/chessgpt-base-v1)
- Chat Version: [chessgpt-chat-v1](https://huggingface.co/Waterhorse/chessgpt-chat-v1)
Also, we are actively working on the development of the next-generatio... | null | [
"apache-2.0"
] | [
"Waterhorse/chess_data"
] | [
"en"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f177630 | b4e60f5ba45df098 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 1,006 | s-nlp/xlmr_formality_classifier | s-nlp | {
"models": [
{
"_id": "621ffdc036468d709f174364",
"id": "FacebookAI/xlm-roberta-base"
}
],
"relation": "finetune"
} | 186 | 88,838 | False | 2022-03-02T23:29:05Z | 2024-10-14T09:53:27Z | transformers | 12 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 278045186}, "total": 278045700} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | d8336084562d7755d9a3e2d5f5d88b9778c6ef7b | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"text-classification",
"formal or informal classification",
"en",
"fr",
"it",
"pt",
"base_model:FacebookAI/xlm-roberta-base",
"base_model:finetune:FacebookAI/xlm-roberta-base",
"license:openrail++",
"text-embeddings-inference",
"en... | null | {"architectures": ["XLMRobertaForSequenceClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": f... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": ["FacebookAI/xlm-roberta-base"], "datasets": null, "eval_results": null, "language": ["en", "fr", "it", "pt"], "library_name": null, "license": "openrail++", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["formal or informal classification"... | **Model Overview**
This is the model presented in the paper ["Detecting Text Formality: A Study of Text Classification Approaches"](https://aclanthology.org/2023.ranlp-1.31/).
XLM-Roberta-based classifier trained on [XFORMAL](https://aclanthology.org/2021.naacl-main.256.bib) -- a multilingual formality classificatio... | null | [
"openrail++",
"cc-by-nc-sa"
] | null | [
"en",
"fr",
"it",
"pt"
] | 278,045,700 | null | null | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65de62ec7facd099b5f5e045 | c201230c641b14d0 | 5cc89648c8003a49 | 256,000 | BPE | 580,604 | true | false | true | true | 4 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 161 | VAGOsolutions/SauerkrautLM-Gemma-7b | VAGOsolutions | null | 165 | 86,314 | False | 2024-02-27T22:32:12Z | 2024-09-30T21:19:09Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"BF16": 8537680896}, "total": 8537680896} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
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"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"... | e67d2e513859a0d92cac28424b3ebd6f6b26e551 | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"sft",
"dpo",
"laserRMT",
"laser-QLoRa",
"finetune",
"work in progress",
"alpha",
"de",
"en",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"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}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["de", "en"], "library_name": null, "license": "other", "license_name": "gemma-terms-of-use", "license_link": "https://ai.google.dev/gemma/terms", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["sft", "dpo", "laserRMT", "laser... | **Update**
- 01.03.2024 - Reuploaded the model in bfloat16 dtype.
- 02.03.2024 - **strongest Gemma finetune model so far: added AGIEval,GPT4ALL and Bigbench scoring with AVG of 54.13 and H6 Open LLM Leaderboard with AVG of 67.83**
![SauerkrautLM](https://vago-solutions.ai/wp-content/uploads/2024/03/sauerkrautgemma.png... | null | [
"other",
"gemma-terms-of-use",
"https://ai.google.dev/gemma/terms"
] | null | [
"de",
"en"
] | 8,537,680,896 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65e4aa71c368fce1336ffe4f | f22022beb599900a | dc748bd59e125412 | 38,000 | BPE | 69,105 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 1,007 | INSAIT-Institute/BgGPT-7B-Instruct-v0.2 | INSAIT-Institute | {
"models": [
{
"_id": "650aedb6238a644cb93a52c3",
"id": "mistralai/Mistral-7B-v0.1"
}
],
"relation": "finetune"
} | 3,884 | 90,693 | False | 2024-03-03T16:50:57Z | 2024-03-06T12:01:16Z | transformers | 25 | 0 | null | text-generation | {"parameters": {"BF16": 7290884096}, "total": 7290884096} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 27d7711b0afb0aa2d5edb6a0b5780aff371b662a | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"instruct",
"bggpt",
"insait",
"conversational",
"bg",
"en",
"base_model:mistralai/Mistral-7B-v0.1",
"base_model:finetune:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
... | 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": "mistralai/Mistral-7B-v0.1", "datasets": null, "eval_results": null, "language": ["bg", "en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["mistral", "instruct", "bggp... | # INSAIT-Institute/BgGPT-7B-Instruct-v0.2
Meet BgGPT-7B, a Bulgarian language model trained from mistralai/Mistral-7B-v0.1. BgGPT is distributed under Apache 2.0 license.
This model was created by [... | null | [
"apache-2.0"
] | null | [
"bg",
"en"
] | 7,290,884,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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