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68680258d532ab10e104b6bd | ef3845a07c8f3846 | 08326fb3abc52f9d | 128,064 | Unigram | null | true | true | true | true | 68 | NFKC | Metaspace | Metaspace | [
"NFKC"
] | [
"Metaspace"
] | [
"Metaspace"
] | 754 | sdadas/polish-reranker-roberta-v3 | sdadas | null | 18,669 | 236,343 | False | 2025-07-04T16:33:28Z | 2026-01-27T19:02:50Z | sentence-transformers | 7 | 0 | null | text-ranking | {"parameters": {"F32": 442891265}, "total": 442891265} | [
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] | e6471da541f4e7be33845b6d57248a8d8bde27e8 | [
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"text-ranking",
"pl",
"license:gemma",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": "pl", "library_name": "sentence-transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-ranking", "tags": ["transformers", "information-retrieval"]} | <h1 align="center">polish-reranker-roberta-v3</h1>
This model is designed to serve as a Polish reranker in retrieval-augmented generation (RAG) pipelines. It is a general-purpose reranker that delivers strong performance across various document types and domains. It is the successor to [**sdadas/polish-reranker-robert... | null | [
"gemma"
] | null | [
"pl"
] | 442,891,265 | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-ranking",
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f17a418 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | daveni/twitter-xlm-roberta-emotion-es | daveni | null | 5,163 | 207,597 | False | 2022-03-02T23:29:05Z | 2022-04-28T09:49:06Z | transformers | 21 | 0 | null | text-classification | null | [
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"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | ab57a1137b2eb1f6c90fc77b0a4c4ced7dbd4d60 | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"Emotion Analysis",
"es",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | 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... | {
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"pipeline_tag": "text-classification",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["es"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["Emotion Analysis"]} | **Note**: This model & model card are based on the [finetuned XLM-T for Sentiment Analysis](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment)
# twitter-XLM-roBERTa-base for Emotion Analysis
This is a XLM-roBERTa-base model trained on ~198M tweets and finetuned for emotion analysis on Spanish langua... | null | null | null | [
"es"
] | null | null | null | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
67590c14e163534a8b199b8b | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | huihui-ai/Llama-3.3-70B-Instruct-abliterated | huihui-ai | {
"models": [
{
"_id": "6745f28f9333dfcc06268b1e",
"id": "meta-llama/Llama-3.3-70B-Instruct"
}
],
"relation": "finetune"
} | 2,550 | 188,768 | False | 2024-12-11T03:50:44Z | 2024-12-12T10:51:13Z | transformers | 67 | 0 | null | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"LICENSE",
"README.md",
"USE_POLICY.md",
"config.json",
"generation_config.json",
"model-00001-of-00030.safetensors",
"model-00002-of-00030.safetensors",
"model-00003-of-00030.safetensors",
"model-00004-of-00030.safetensors",
"model-00005-of-00030.safetensors",
"model-00006-o... | fa13334669544bab573e0e5313cad629a9c02e2c | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"abliterated",
"uncensored",
"conversational",
"en",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"de",
"base_model:meta-llama/Llama-3.3-70B-Instruct",
"base_model:finetune:meta-llama/... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["meta-llama/Llama-3.3-70B-Instruct"], "datasets": null, "eval_results": null, "language": ["en", "fr", "it", "pt", "hi", "es", "th", "de"], "library_name": "transformers", "license": "llama3.3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags"... | # huihui-ai/Llama-3.3-70B-Instruct-abliterated
This is an uncensored version of [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more ab... | null | [
"llama3.3"
] | null | [
"en",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"de"
] | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65acdd84819fbfaf491d7620 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | yunconglong/Truthful_DPO_TomGrc_FusionNet_7Bx2_MoE_13B | yunconglong | null | 12,245 | 237,816 | False | 2024-01-21T09:01:56Z | 2024-02-28T02:15:25Z | transformers | 53 | 0 | null | text-generation | {"parameters": {"BF16": 12879138816}, "total": 12879138816} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00006.safetensors",
"model-00002-of-00006.safetensors",
"model-00003-of-00006.safetensors",
"model-00004-of-00006.safetensors",
"model-00005-of-00006.safetensors",
"model-00006-of-00006.safetensors",
"model.s... | dd66c98fa56ab95e321e591f123081ab4296a032 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"DPO",
"RL-TUNED",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<s>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["moe", "DPO", "RL-TUNED"]} | * [DPO Trainer](https://huggingface.co/docs/trl/main/en/dpo_trainer) with dataset jondurbin/truthy-dpo-v0.1 to improve [TomGrc/FusionNet_7Bx2_MoE_14B]
```
DPO Trainer
TRL supports the DPO Trainer for training language models from preference data, as described in the paper Direct Preference Optimization: Your Languag... | null | [
"mit"
] | null | null | 12,879,138,816 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
643f4d908d9a6e3bba3c5d22 | 4d406ecdc78060d6 | dc30b321a6b44822 | 50,280 | BPE | 50,009 | true | true | true | true | 28 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 670 | stabilityai/stablelm-tuned-alpha-3b | stabilityai | null | 2,426 | 188,841 | False | 2023-04-19T02:10:24Z | 2023-04-19T12:38:16Z | transformers | 110 | 0 | null | text-generation | null | [
".gitattributes",
"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"
] | d1c03d2114451d562416b9efe4281d319ceff99e | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"causal-lm",
"en",
"dataset:dmayhem93/ChatCombined",
"dataset:tatsu-lab/alpaca",
"dataset:nomic-ai/gpt4all_prompt_generations",
"dataset:Dahoas/full-hh-rlhf",
"dataset:jeffwan/sharegpt_vicuna",
"dataset:HuggingFaceH4/databricks_dolly_15... | 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": ["dmayhem93/ChatCombined", "tatsu-lab/alpaca", "nomic-ai/gpt4all_prompt_generations", "Dahoas/full-hh-rlhf", "jeffwan/sharegpt_vicuna", "HuggingFaceH4/databricks_dolly_15k"], "eval_results": null, "language": ["en"], "library_name": null, "license": ["cc-by-nc-sa-4.0"], "license_name": ... | # StableLM-Tuned-Alpha
## Model Description
`StableLM-Tuned-Alpha` is a suite of 3B and 7B parameter decoder-only language models built on top of the `StableLM-Base-Alpha` models and further fine-tuned on various chat and instruction-following datasets.
## Usage
Get started chatting with `StableLM-Tuned-Alpha` by u... | null | [
"cc-by-nc-sa-4.0"
] | [
"dmayhem93/ChatCombined",
"tatsu-lab/alpaca",
"nomic-ai/gpt4all_prompt_generations",
"Dahoas/full-hh-rlhf",
"jeffwan/sharegpt_vicuna",
"HuggingFaceH4/databricks_dolly_15k"
] | [
"en"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
634f1f092cd84978c49504ae | f01edcaae62c5252 | bdd8c6446a87e77f | 32,102 | Unigram | null | true | true | true | true | 105 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 634 | microsoft/GODEL-v1_1-base-seq2seq | microsoft | null | 117 | 180,422 | False | 2022-10-18T21:47:53Z | 2023-01-24T17:18:38Z | transformers | 70 | 0 | null | null | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
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"tokenizer_config.json"
] | 728a30c885f2bcaa14d34a3401bb62f64ca2afcc | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"conversational",
"arxiv:2206.11309",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"], "thumbnail": "https://huggingface.co/front/thumbnails/dialogpt.png"} | ### Large-Scale Pre-Training for Goal-Directed Dialog (GODEL)
GODEL is a large-scale pre-trained model for goal-directed dialogs. It is parameterized with a Transformer-based encoder-decoder model and trained for response generation grounded in external text, which allows more effective fine-tuning on dialog tasks tha... | null | [
"mit"
] | null | null | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
65b6a552d73977130c539452 | 002e93bda29b6e9c | dddad82cb50bdb30 | 32,005 | BPE | 58,980 | true | false | true | true | 8 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 755 | artek0chumak/TestMixtral | artek0chumak | null | 817 | 207,969 | False | 2024-01-28T19:04:50Z | 2024-09-20T10:50:08Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"F32": 6608064}, "total": 6608064} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | c62b7081d600804c1431fe43ba7888fbaa27f8c4 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"arxiv:1910.09700",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<|bos|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": []} | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated... | null | null | null | null | 6,608,064 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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621ffdc136468d709f17f308 | 8a476fd884d4dddf | d965e4a9140ecf72 | 21,128 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 756 | raynardj/classical-chinese-punctuation-guwen-biaodian | raynardj | null | 456 | 180,827 | False | 2022-03-02T23:29:05Z | 2025-10-28T07:33:58Z | transformers | 26 | 0 | null | token-classification | {"parameters": {"I64": 512, "F32": 101693205}, "total": 101693717} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | df9601e08f001f8a18fd6bcd80f87d00b2f53d94 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"ner",
"punctuation",
"古文",
"文言文",
"ancient",
"classical",
"zh",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["ner", "punctuation", "\u53e4\u6587", "\u6587\u8a00\u6587", "ancient", "classical"], "wi... | # Classical Chinese Punctuation
> 欢迎前往[我的github文言诗词项目页面探讨、加⭐️ ](https://github.com/raynardj/yuan)， Please check the github repository for more about the [model, hit 🌟 if you like](https://github.com/raynardj/yuan)
* This model punctuates Classical(ancient) Chinese, you might feel strange about this task, but **many... | null | null | null | [
"zh"
] | 101,693,717 | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
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] | 309 | TheBloke/Nous-Hermes-Llama2-GPTQ | TheBloke | {
"models": [
{
"_id": "64b9c26596676e40d0f3983d",
"id": "NousResearch/Nous-Hermes-Llama2-13b"
}
],
"relation": "quantized"
} | 32 | 178,853 | False | 2023-07-21T21:33:03Z | 2023-09-27T12:44:58Z | transformers | 60 | 0 | null | text-generation | {"parameters": {"F32": 2560, "I32": 12687769600, "BF16": 328422400, "F16": 2129920}, "total": 13018324480} | [
".gitattributes",
"LICENSE.txt",
"Notice",
"README.md",
"USE_POLICY.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model.safetensors",
"quantize_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | d0b6c71fadcd215acf99f5601965b7726fa435a0 | [
"transformers",
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"llama",
"text-generation",
"llama-2",
"self-instruct",
"distillation",
"synthetic instruction",
"en",
"base_model:NousResearch/Nous-Hermes-Llama2-13b",
"base_model:quantized:NousResearch/Nous-Hermes-Llama2-13b",
"license:mit",
"text-generation-inference",
"4... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "cont... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "NousResearch/Nous-Hermes-Llama2-13b", "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": ["mit"], "license_name": null, "license_link": null, "metrics": null, "model_name": "Nous Hermes Llama 2 13B", "pipeline_tag": null, "tags": ["llama-2", "self-instruct", "di... | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<d... | null | [
"mit"
] | null | [
"en"
] | 13,018,324,480 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
679ca34d8d7a716dcf837a70 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | unsloth/Qwen2.5-VL-7B-Instruct | unsloth | {
"models": [
{
"_id": "6795ffcd88cd7c0294702a72",
"id": "Qwen/Qwen2.5-VL-7B-Instruct"
}
],
"relation": "finetune"
} | 16,683 | 244,040 | False | 2025-01-31T10:17:49Z | 2025-09-16T15:19:43Z | transformers | 16 | 0 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"chat_template.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors"... | cbb81dca0b8c1a0c6827913deda2709388acadde | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"multimodal",
"unsloth",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",... | null | {"architectures": ["Qwen2_5_VLForConditionalGeneration"], "model_type": "qwen2_5_vl", "processor_config": {"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a h... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["Qwen/Qwen2.5-VL-7B-Instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ["multimodal", "unsloth"]} | # Qwen2.5-VL-7B-Instruct
<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Introduction
In the past five months since Qwen2-VL’s r... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"qwen2_5_vl",
"AutoModelForImageTextToText",
"Qwen2_5_VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
66eb5406d60aa330081dbaea | 643d190440f20cd9 | 84110b1ed2b9294f | 151,666 | BPE | 151,387 | true | true | true | true | 23 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 493 | unsloth/Qwen2.5-32B-Instruct-bnb-4bit | unsloth | {
"models": [
{
"_id": "66e902f34eeaced24a2787f8",
"id": "Qwen/Qwen2.5-32B-Instruct"
}
],
"relation": "quantized"
} | 20,118 | 243,043 | False | 2024-09-18T22:28:22Z | 2025-04-28T04:16:05Z | transformers | 14 | 0 | null | text-generation | {"parameters": {"F32": 2026496, "BF16": 1558254592, "U8": 32180952074}, "total": 33741233162} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_to... | aa79e3472818bdec779075d80928602591d9f2a0 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"conversational",
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:q... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-32B-Instruct", "datasets": null, "eval_results": null, "language": ["zho", "eng", "fra", "spa", "por", "deu", "ita", "rus", "jpn", "kor", "vie", "tha", "ara"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name":... | # Finetune Llama 3.1, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a Qwen 2.5 (all model sizes) [free Google Colab Tesla T4 notebook](https://colab.research.google.com/drive/1Kose-ucXO1IBaZq5BvbwWieuubP7hxvQ?usp=sharing).
Also a [Qwen 2.5 conversational style notebook](https://colab.resear... | null | [
"apache-2.0"
] | null | [
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara"
] | 33,741,233,162 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1816b9 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | wietsedv/xlm-roberta-base-ft-udpos28-en | wietsedv | null | 17 | 178,165 | False | 2022-03-02T23:29:05Z | 2023-09-11T08:56:04Z | transformers | 3 | 0 | [{"name": "xlm-roberta-base-ft-udpos28-en", "results": [{"task": {"type": "token-classification", "name": "Part-of-Speech Tagging"}, "dataset": {"type": "universal_dependencies", "name": "Universal Dependencies v2.8"}, "metrics": [{"type": "accuracy", "name": "English Test accuracy", "value": 96, "verified": false}, {"... | token-classification | {"parameters": {"I64": 514, "F32": 277466129}, "total": 277466643} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train.args"
] | 281f4cb9aadaf08dd174a7ebe60cd34957fb49d8 | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"en",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaForTokenClassification"], "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": fals... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["universal_dependencies"], "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "metrics": ["accuracy"], "tags": ["part-of-speech", "token-classification"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-en", "results": [{"task": {"type": "token-classification", "name": "Par... | # XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: English
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | null | [
"apache-2.0"
] | [
"universal_dependencies"
] | [
"en"
] | 277,466,643 | null | [
"accuracy"
] | [
"XLMRobertaForTokenClassification",
"AutoModelForTokenClassification",
"xlm-roberta"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6364c64d8b6bd0d9f654c6f9 | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | google/switch-base-64 | google | null | 92 | 178,748 | False | 2022-11-04T07:59:09Z | 2023-01-24T17:19:59Z | transformers | 3 | 0 | null | null | null | [
".gitattributes",
"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",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | b9fae596288a4a26289db5b28ab014b93fe5b9a9 | [
"transformers",
"pytorch",
"switch_transformers",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2101.03961",
"arxiv:1910.09700",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["SwitchTransformersForConditionalGeneration"], "model_type": "switch_transformers", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["c4"], "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": ["text2text-generation"], "widget": [{"text": "The <extra_id_0> walks in <extra... | # Model Card for Switch Transformers Base - 64 experts
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Usage](#usage)
3. [Uses](#uses)
4. [Bias, Risks, and Limitations](#bias-r... | null | [
"apache-2.0"
] | [
"c4"
] | [
"en"
] | null | null | null | [
"AutoModelForSeq2SeqLM",
"SwitchTransformersForConditionalGeneration",
"switch_transformers"
] | [
"text2text-generation"
] | null | null | null |
621ffdc136468d709f17a906 | 11f42d645cdf6935 | b1b9df52da7479f6 | 50,000 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 757 | dumitrescustefan/bert-base-romanian-ner | dumitrescustefan | null | 6,768 | 215,775 | False | 2022-03-02T23:29:05Z | 2025-04-09T12:33:00Z | transformers | 5 | 0 | null | token-classification | {"parameters": {"I64": 512, "F32": 123874591}, "total": 123875103} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | ad882307d75757bdc900d4c2e53455b497250aa6 | [
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"safetensors",
"bert",
"token-classification",
"ro",
"dataset:ronec",
"arxiv:1909.01247",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["ronec"], "eval_results": null, "language": "ro", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | null | [
"mit"
] | [
"ronec"
] | [
"ro"
] | 123,875,103 | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6643bc70bc86c9465b549e36 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | w601sxs/b1ade-embed | w601sxs | {
"models": [
{
"_id": "64fff5087f91f94040eee912",
"id": "BAAI/bge-large-en-v1.5"
}
],
"relation": "finetune"
} | 421 | 180,707 | False | 2024-05-14T19:33:04Z | 2025-03-12T17:29:50Z | transformers | 5 | 0 | [{"name": "merged_model", "results": [{"task": {"type": "Classification"}, "dataset": {"type": "mteb/amazon_counterfactual", "name": "MTEB AmazonCounterfactualClassification (en)", "config": "en", "split": "test", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205"}, "metrics": [{"type": "accuracy", "value": 75.1791... | feature-extraction | null | [
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".ipynb_checkpoints/README-checkpoint.md",
".ipynb_checkpoints/config-checkpoint.json",
"README.md",
"config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | ee4c9b262a551a94502063f8224f08a7349762e1 | [
"transformers",
"safetensors",
"bert",
"feature-extraction",
"mteb",
"base_model:BAAI/bge-large-en-v1.5",
"base_model:finetune:BAAI/bge-large-en-v1.5",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": ["bert-large-uncased", "WhereIsAI/UAE-Large-V1", "BAAI/bge-large-en-v1.5", "mixedbread-ai/mxbai-embed-large-v1", "avsolatorio/GIST-large-Embedding-v0"], "library_name": "transformers", "tags": ["mteb"], "model-index": [{"name": "merged_model", "results": [{"task": {"type": "Classification"}, "dataset": {... | `b1ade-embed` is a small but efficient embedding model for RAG. In the legacy MTEB leaderboard ( - 2024) b1ade-embed was ranked #1 in the STS catagory and placed competitively for other important task categories such as ranking, retrieval and classification. The model was trained using a combination of:
1. Model mergi... | null | null | null | null | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
64c5803ee77ea9f2813e599d | ebd6c9c30ae00df3 | 3085d01101e6b8e8 | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 758 | kartashoffv/vashkontrol-sentiment-rubert | kartashoffv | {
"models": [
{
"_id": "621ffdc036468d709f175167",
"id": "DeepPavlov/rubert-base-cased"
}
],
"relation": "finetune"
} | 22 | 237,574 | False | 2023-07-29T21:10:22Z | 2023-08-06T15:44:16Z | transformers | 2 | 0 | [{"name": "vashkontrol-sentiment-rubert", "results": []}] | text-classification | {"parameters": {"F32": 177855747}, "total": 177855747} | [
".gitattributes",
".gitignore",
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"model.safetensors",
"pytorch_model.bin",
"runs/Jul29_21-10-11_15674fd32346/events.out.tfevents.1690665032.15674fd32346.372.0",
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"bert",
"text-classification",
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"sentiment",
"ru",
"dataset:kartashoffv/vash_kontrol_reviews",
"base_model:DeepPavlov/rubert-base-cased",
"base_model:finetune:DeepPavlov/rubert-base-cased",
"license:mit",
"te... | 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": "DeepPavlov/rubert-base-cased", "datasets": ["kartashoffv/vash_kontrol_reviews"], "eval_results": [], "language": ["ru"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": ["f1"], "model_name": "vashkontrol-sentiment-rubert", "pipeline_tag": "text-classificati... | # Sentimental assessment of portal reviews "VashKontrol"
The model is designed to evaluate the tone of reviews from the [VashKontrol portal](https://vashkontrol.ru/).
This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on a following dataset: [kart... | null | [
"mit"
] | [
"kartashoffv/vash_kontrol_reviews"
] | [
"ru"
] | 177,855,747 | null | [
"f1"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65e7b07a767bfc7d10aec444 | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | state-spaces/mamba-2.8b-hf | state-spaces | null | 10,170 | 216,884 | False | 2024-03-05T23:53:30Z | 2024-03-06T00:44:55Z | transformers | 111 | 0 | null | text-generation | {"parameters": {"F32": 2768345600}, "total": 2768345600} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"tokenizer.json",
"tokenizer_config.json"
] | 96c48e0292b63f5346b6d30061af2551f7101e26 | [
"transformers",
"safetensors",
"mamba",
"text-generation",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MambaForCausalLM"], "model_type": "mamba", "tokenizer_config": {"bos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": []} | # Mamba
<!-- Provide a quick summary of what the model is/does. -->
This repository contains the `transfromers` compatible `mamba-2.8b`. The checkpoints are untouched, but the full `config.json` and tokenizer are pushed to this repo.
# Usage
You need to install `transformers` from `main` until `transformers=4.39.0`... | null | null | null | null | 2,768,345,600 | null | null | [
"AutoModelForCausalLM",
"mamba",
"MambaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66b5c0b997e4b186a068ae9e | 827f6451ef99df30 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 355 | upskyy/e5-large-korean | upskyy | {
"models": [
{
"_id": "649e866b9badc2e0a464292e",
"id": "intfloat/multilingual-e5-large"
}
],
"relation": "finetune"
} | 30 | 186,595 | False | 2024-08-09T07:09:45Z | 2024-08-09T07:38:27Z | sentence-transformers | 3 | 0 | [{"name": "upskyy/e5-large-korean", "results": [{"task": {"type": "semantic-similarity", "name": "Semantic Similarity"}, "dataset": {"name": "sts dev", "type": "sts-dev"}, "metrics": [{"type": "pearson_cosine", "value": 0.8710078333363093, "name": "Pearson Cosine", "verified": false}, {"type": "spearman_cosine", "value... | sentence-similarity | {"parameters": {"F32": 559890432}, "total": 559890432} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"model.safetensors",
"modules.json",
"sentence_bert_config.json",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | ff39d879a71a6951b46f6b282e7968db29f3778f | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"feature-extraction",
"korean",
"transformers",
"multilingual",
"sentence-similarity",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
... | null | {"architectures": ["XLMRobertaModel"], "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": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": "intfloat/multilingual-e5-large", "datasets": [], "language": ["multilingual", "af", "am", "ar", "as", "az", "be", "bg", "bn", "br", "bs", "ca", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "he", "hi", "hr", "hu", "hy", "id", "is", "it"... | # upskyy/e5-large-korean
This model is korsts and kornli finetuning model from [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mi... | null | [
"mit"
] | null | [
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha",
"he",
"hi",
"hr",
"hu",
"hy",
"id",
"is",
"i... | 559,890,432 | null | [
"pearson_cosine",
"spearman_cosine",
"pearson_manhattan",
"spearman_manhattan",
"pearson_euclidean",
"spearman_euclidean",
"pearson_dot",
"spearman_dot",
"pearson_max",
"spearman_max"
] | [
"XLMRobertaModel",
"AutoModel",
"xlm-roberta"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
66170f1742b027d6b7567eec | 0566decb107ef807 | 656a765e42bb964a | 33,152 | BPE | 60,675 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 381 | dicta-il/dictalm2.0 | dicta-il | null | 5,551 | 201,416 | False | 2024-04-10T22:13:43Z | 2024-07-10T16:05:57Z | transformers | 25 | 0 | null | text-generation | {"parameters": {"BF16": 7251169280}, "total": 7251169280} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.... | f8ab3208e95a7b44a9a2fbb9bbbdd8ea11be509d | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"pretrained",
"en",
"he",
"arxiv:2407.07080",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "he"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["pretrained"], "inference": {"parameters": {"temperature": 0.... | [<img src="https://i.ibb.co/5Lbwyr1/dicta-logo.jpg" width="300px"/>](https://dicta.org.il)
# Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities
The DictaLM-2.0 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters trained to specia... | null | [
"apache-2.0"
] | null | [
"en",
"he"
] | 7,251,169,280 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67459f248ea6308b5fdd8698 | 2d0341bd3a73bae6 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 32 | peft-internal-testing/tiny-T5ForConditionalGeneration | peft-internal-testing | null | 28,335 | 256,540 | False | 2024-11-26T10:12:52Z | 2024-11-26T10:16:31Z | transformers | 0 | 0 | null | null | {"parameters": {"F32": 559280}, "total": 559280} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | 3340286a49a0591bb4b8c2bcb57bda5ba00216be | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"trl",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["trl"]} | # Tiny T5ForConditionalGeneration
PEFT copy of trl-internal-testing/tiny-T5ForConditionalGeneration, minimal model built for unit tests. | null | null | null | null | 559,280 | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
64415d384c2acf3398a63324 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | severinsimmler/xlm-roberta-longformer-base-16384 | severinsimmler | null | 6,733 | 199,270 | False | 2023-04-20T15:41:44Z | 2023-07-10T22:15:52Z | transformers | 29 | 0 | [{"name": "xlm-roberta-longformer-base-16384", "results": []}] | feature-extraction | {"parameters": {"F32": 311494656}, "total": 311494656} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 859ef84305e96f73f61b3ce9f2d44892421a8965 | [
"transformers",
"pytorch",
"safetensors",
"longformer",
"feature-extraction",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"g... | null | {"architectures": ["LongformerModel"], "model_type": "longformer", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": {"__type": "AddedToken", "content": "<mask>", "lstrip": true, "normalized": true, "rstrip": false, "single_word": false}, "pad_token": "<pad>", "sep_token": ... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": ["multilingual", "af", "am", "ar", "as", "az", "be", "bg", "bn", "br", "bs", "ca", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "he", "hi", "hr", "hu", "hy", "id", "is", "it", "ja"... | # xlm-roberta-longformer-base-16384
⚠️ This is just the PyTorch version of [`hyperonym/xlm-roberta-longformer-base-16384`](https://huggingface.co/hyperonym/xlm-roberta-longformer-base-16384) without any modifications.
**xlm-roberta-longformer** is a multilingual [Longformer](https://arxiv.org/abs/2004.05150) initiali... | null | [
"mit"
] | null | [
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha",
"he",
"hi",
"hr",
"hu",
"hy",
"id",
"is",
"i... | 311,494,656 | null | null | [
"AutoModel",
"longformer",
"LongformerModel"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
64ee239f7ce493905c7c8d2d | 325a424394535720 | b927f436c0f7aef5 | 128,000 | WordPiece | null | true | true | true | false | 6 | Sequence | Split | null | [
"NFD",
"Lowercase",
"StripAccents",
"Replace",
"Replace"
] | [
"Split"
] | null | 613 | dicta-il/dictabert | dicta-il | null | 1,866 | 191,857 | False | 2023-08-29T16:58:07Z | 2023-12-28T07:39:07Z | transformers | 12 | 0 | null | fill-mask | {"parameters": {"I64": 512, "F32": 184474880}, "total": 184475392} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 8884c6db002aba4002ee638fe4070c92e9ffbbf1 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"fill-mask",
"he",
"arxiv:2308.16687",
"license:cc-by-4.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["he"], "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew
State-of-the-art language model for Hebrew, released [here](https://arxiv.org/abs/2308.16687).
This is the base model pretrained with the masked-language-modeling objective.
For the bert-base models for other tasks, see [here](https://huggingface.co/colle... | null | [
"cc-by-4.0"
] | null | [
"he"
] | 184,475,392 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
645f575325a4075bcf994ff6 | d89a849b034c270f | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 510 | TheBloke/Wizard-Vicuna-13B-Uncensored-HF | TheBloke | null | 969 | 181,198 | False | 2023-05-13T09:24:35Z | 2023-06-05T00:10:10Z | transformers | 214 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00003.bin",
"pytorch_model-00002-of-00003.bin",
"pytorch_model-00003-of-00003.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.... | fff9ac7f0e2e7b340f2301f5f089d989fc03be67 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"uncensored",
"en",
"dataset:ehartford/wizard_vicuna_70k_unfiltered",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["ehartford/wizard_vicuna_70k_unfiltered"], "eval_results": null, "language": ["en"], "library_name": null, "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["uncensored"], "inference": true} | <!-- header start -->
<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 | [
"other"
] | [
"ehartford/wizard_vicuna_70k_unfiltered"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
667d2b521bc19f3923b551fe | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | MaziyarPanahi/calme-2.3-qwen2-7b | MaziyarPanahi | {
"models": [
{
"_id": "665f181fb9e194a20c5e8d44",
"id": "Qwen/Qwen2-7B"
}
],
"relation": "finetune"
} | 36 | 175,585 | False | 2024-06-27T09:05:22Z | 2024-09-19T11:23:38Z | transformers | 2 | 0 | [{"name": "calme-2.3-qwen2-7b", "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": 38.25, "name": "strict accu... | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"qwen2-fine... | 3eafb915a0ba9a3f0c1c64c760ee901bef8c8206 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"qwen",
"finetune",
"chatml",
"OpenHermes-2.5",
"HelpSteer2",
"Orca",
"SlimOrca",
"conversational",
"en",
"dataset:nvidia/HelpSteer2",
"dataset:teknium/OpenHermes-2.5",
"dataset:microsoft/orca-math-word-problems-200k"... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-7B", "datasets": ["nvidia/HelpSteer2", "teknium/OpenHermes-2.5", "microsoft/orca-math-word-problems-200k", "Open-Orca/SlimOrca"], "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "pipeline_tag": "text-generation", "tags": ["chat", "qwen", "qwen2", "finetune", "chat... | <img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# MaziyarPanahi/calme-2.3-qwen2-7b
This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.
# ⚡ Quantized GGU... | null | [
"apache-2.0"
] | [
"nvidia/HelpSteer2",
"teknium/OpenHermes-2.5",
"microsoft/orca-math-word-problems-200k",
"Open-Orca/SlimOrca"
] | [
"en"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66f6c2e1584cae45b567a3b5 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | chuanli11/Llama-3.2-3B-Instruct-uncensored | chuanli11 | null | 758 | 182,115 | False | 2024-09-27T14:36:17Z | 2024-10-18T04:56:29Z | transformers | 150 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 27bd02b95b56f9886daf3d4be4101916b15809d1 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2406.11717",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": []} | # Llama-3.2-3B-Instruct-uncensored
### Disclaimer
This model is intended for research purposes only and may produce inaccurate or unreliable outputs. Use it cautiously and at your own risk.
<p align="center">
🦄 Other exciting ML projects at Lambda: <a href="https://news.lambda... | null | null | null | null | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
667d2d204c65c3334cce5414 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | MaziyarPanahi/calme-2.4-qwen2-7b | MaziyarPanahi | {
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{
"_id": "665f181fb9e194a20c5e8d44",
"id": "Qwen/Qwen2-7B"
}
],
"relation": "finetune"
} | 36 | 175,508 | False | 2024-06-27T09:13:04Z | 2024-09-19T11:24:06Z | transformers | 1 | 0 | [{"name": "calme-2.4-qwen2-7b", "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": 33, "name": "strict accurac... | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
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"qwen2-fine... | 0ea4c2a318e70054a403b911385c11aa5a4a4ff3 | [
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"en",
"dataset:nvidia/HelpSteer2",
"dataset:teknium/OpenHermes-2.5",
"dataset:microsoft/orca-math-word-problems-200k"... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"base_model": "Qwen/Qwen2-7B", "datasets": ["nvidia/HelpSteer2", "teknium/OpenHermes-2.5", "microsoft/orca-math-word-problems-200k", "Open-Orca/SlimOrca"], "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "pipeline_tag": "text-generation", "tags": ["chat", "qwen", "qwen2", "finetune", "chat... | <img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# MaziyarPanahi/calme-2.4-qwen2-7b
This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.
# ⚡ Quantized GGU... | null | [
"apache-2.0"
] | [
"nvidia/HelpSteer2",
"teknium/OpenHermes-2.5",
"microsoft/orca-math-word-problems-200k",
"Open-Orca/SlimOrca"
] | [
"en"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
667d2f0501587f36631f1269 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
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"models": [
{
"_id": "665f181fb9e194a20c5e8d44",
"id": "Qwen/Qwen2-7B"
}
],
"relation": "finetune"
} | 41 | 175,327 | False | 2024-06-27T09:21:09Z | 2024-07-21T11:34:10Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
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"qwen2-fine... | 20fb1afc22c0722cb2c57185fff59befeba0fbec | [
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"OpenHermes-2.5",
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"conversational",
"en",
"dataset:nvidia/HelpSteer2",
"dataset:teknium/OpenHermes-2.5",
"dataset:microsoft/orca-math-word-problems-200k"... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-7B", "datasets": ["nvidia/HelpSteer2", "teknium/OpenHermes-2.5", "microsoft/orca-math-word-problems-200k", "Open-Orca/SlimOrca"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "mo... | <img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# MaziyarPanahi/calme-2.5-qwen2-7b
This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.
# ⚡ Quantized GGU... | null | [
"apache-2.0"
] | [
"nvidia/HelpSteer2",
"teknium/OpenHermes-2.5",
"microsoft/orca-math-word-problems-200k",
"Open-Orca/SlimOrca"
] | [
"en"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
667d2fa3d50b1e0c3ca1aa72 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | MaziyarPanahi/calme-2.6-qwen2-7b | MaziyarPanahi | {
"models": [
{
"_id": "665f181fb9e194a20c5e8d44",
"id": "Qwen/Qwen2-7B"
}
],
"relation": "finetune"
} | 34 | 175,294 | False | 2024-06-27T09:23:47Z | 2024-07-21T11:29:10Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
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"dataset:nvidia/HelpSteer2",
"dataset:teknium/OpenHermes-2.5",
"dataset:microsoft/orca-math-word-problems-200k"... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-7B", "datasets": ["nvidia/HelpSteer2", "teknium/OpenHermes-2.5", "microsoft/orca-math-word-problems-200k", "Open-Orca/SlimOrca"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "mo... | <img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# MaziyarPanahi/calme-2.6-qwen2-7b
This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.
# ⚡ Quantized GGU... | null | [
"apache-2.0"
] | [
"nvidia/HelpSteer2",
"teknium/OpenHermes-2.5",
"microsoft/orca-math-word-problems-200k",
"Open-Orca/SlimOrca"
] | [
"en"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64fa854320a2d04cc165845d | b8a1cdd978ebb3ce | 2bc23d266c63598f | 37,632 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 759 | OpenBuddy/openbuddy-codellama2-34b-v11.1-bf16 | OpenBuddy | null | 804 | 179,733 | False | 2023-09-08T02:21:55Z | 2023-09-20T06:40:58Z | transformers | 11 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00007.bin",
"pytorch_model-00002-of-00007.bin",
"pytorch_model-00003-of-00007.bin",
"pytorch_model-00004-of-00007.bin",
"pytorch_model-00005-of-00007.bin",
"pytorch_model-00006-of-00007.bin",
"pytorch... | 1b361b3634bf59913b47c9dad1b138e99833472b | [
"transformers",
"pytorch",
"llama",
"text-generation",
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru",
"text-generation-inference",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh", "en", "fr", "de", "ja", "ko", "it", "ru"], "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "inference": false... | # 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)
# Copyright Notice
This ... | null | null | null | [
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
680efb2669de8e16a77a54cf | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | unsloth/Qwen3-8B | unsloth | {
"models": [
{
"_id": "680da79d48c19d19cf82ab5e",
"id": "Qwen/Qwen3-8B"
}
],
"relation": "finetune"
} | 94,903 | 491,383 | False | 2025-04-28T03:51:02Z | 2025-05-13T20:19:42Z | transformers | 16 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"configuration.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors"... | 946bc9ac74a6c1f8cf012497c503a119b2fcf2eb | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"unsloth",
"conversational",
"arxiv:2309.00071",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"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/Qwen3-8B"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "ta... | # Qwen3-8B
<a href="https://chat.qwen.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Qwen3 Highlights
Qwen3 is the latest generation of large language model... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
667d31736c001a47ec76926b | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | MaziyarPanahi/calme-2.7-qwen2-7b | MaziyarPanahi | {
"models": [
{
"_id": "665f181fb9e194a20c5e8d44",
"id": "Qwen/Qwen2-7B"
}
],
"relation": "finetune"
} | 30 | 174,980 | False | 2024-06-27T09:31:31Z | 2024-09-19T11:32:23Z | transformers | 2 | 0 | [{"name": "calme-2.7-qwen2-7b", "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": 35.92, "name": "strict accu... | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
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"config.json",
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"model.safetensors.index.json",
"qwen2-fine... | ff4b5dbac8898e0148a48ebf9de613b11cbbe439 | [
"transformers",
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"qwen2",
"text-generation",
"chat",
"qwen",
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"chatml",
"OpenHermes-2.5",
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"conversational",
"en",
"dataset:nvidia/HelpSteer2",
"dataset:teknium/OpenHermes-2.5",
"dataset:microsoft/orca-math-word-problems-200k"... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-7B", "datasets": ["nvidia/HelpSteer2", "teknium/OpenHermes-2.5", "microsoft/orca-math-word-problems-200k", "Open-Orca/SlimOrca"], "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "pipeline_tag": "text-generation", "tags": ["chat", "qwen", "qwen2", "finetune", "chat... | <img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# MaziyarPanahi/calme-2.7-qwen2-7b
This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.
# ⚡ Quantized GGU... | null | [
"apache-2.0"
] | [
"nvidia/HelpSteer2",
"teknium/OpenHermes-2.5",
"microsoft/orca-math-word-problems-200k",
"Open-Orca/SlimOrca"
] | [
"en"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
656e2f010f21e03bc8768ad3 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | togethercomputer/StripedHyena-Nous-7B | togethercomputer | null | 142 | 175,077 | False | 2023-12-04T19:56:49Z | 2024-03-27T19:15:38Z | transformers | 143 | 0 | null | text-generation | {"parameters": {"F16": 7646024704}, "total": 7646024704} | [
".gitattributes",
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"model-00002-of-00002.safetensors",
"model.py",
"model.safetensors.index.json",
"modeling_hyena.py",
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"pytorch",
"safetensors",
"stripedhyena",
"text-generation",
"custom_code",
"en",
"arxiv:2302.10866",
"arxiv:2310.18780",
"arxiv:2311.05908",
"doi:10.57967/hf/1595",
"license:apache-2.0",
"region:us"
] | null | {"model_type": "stripedhyena", "architectures": ["StripedHyenaModelForCausalLM"], "auto_map": {"AutoConfig": "togethercomputer/StripedHyena-Nous-7B--configuration_hyena.StripedHyenaConfig", "AutoModelForCausalLM": "togethercomputer/StripedHyena-Nous-7B--modeling_hyena.StripedHyenaModelForCausalLM"}, "tokenizer_config":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "togethercomputer/StripedHyena-Nous-7B--modeling_hyena.StripedHyenaModelForCausalLM",
"pipeline_tag": "text-generation",
"processor": null
} | {"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": null} | ## StripedHyena-Nous-7B (SH-N 7B)
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/62a1306bbe7fa896d2c8de44/Bfjh77emDsWOY-VmfvU9C.png" width="60%" />
</p>
### About
One of the focus areas at Together Research is new architectures for long context, improved training, and inference... | null | [
"apache-2.0"
] | null | [
"en"
] | 7,646,024,704 | null | null | [
"AutoModelForCausalLM",
"StripedHyenaModelForCausalLM",
"togethercomputer/StripedHyena-Nous-7B--modeling_hyena.StripedHyenaModelForCausalLM",
"stripedhyena"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6492543d75ead03082a1ed72 | 7903ca758156b287 | ffae8233e53a99e4 | 256,204 | BPE | 514,098 | true | true | true | true | 207 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 60 | winstxnhdw/nllb-200-distilled-1.3B-ct2-int8 | winstxnhdw | null | 108 | 176,126 | False | 2023-06-21T01:37:01Z | 2025-09-28T03:36:35Z | transformers | 6 | 0 | null | translation | null | [
".gitattributes",
"README.md",
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null,
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6524eba89d870c61b3102f8e | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | uukuguy/speechless-code-mistral-7b-v1.0 | uukuguy | null | 8,475 | 215,648 | False | 2023-10-10T06:14:00Z | 2023-12-30T11:27:23Z | transformers | 18 | 0 | [{"name": "SpeechlessCoder", "results": [{"task": {"type": "text-generation"}, "dataset": {"type": "openai_humaneval", "name": "HumanEval"}, "metrics": [{"name": "pass@1", "type": "pass@1", "value": 51.21951219512195, "verified": false}]}]}] | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
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"pytorch_model-00001-of-00002.bin",
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"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
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] | 1862e0a712efc6002112e9c1235a197d58419b37 | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"code",
"en",
"dataset:jondurbin/airoboros-2.2",
"dataset:Open-Orca/OpenOrca",
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"dataset:WizardLM/WizardLM_evol_instruct_V2_196k",
"dataset:TokenBender/python_eval_instruct_51k",
"license:apache-2.0",... | 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",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["jondurbin/airoboros-2.2", "Open-Orca/OpenOrca", "garage-bAInd/Open-Platypus", "WizardLM/WizardLM_evol_instruct_V2_196k", "TokenBender/python_eval_instruct_51k"], "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "pipeline_tag": "text-generation", "tags": ["code"], "model-index"... | <p><h1> speechless-code-mistral-7b-v1.0 </h1></p>
* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-AWQ)
* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-GPTQ)
* [2, 3, 4, ... | null | [
"apache-2.0"
] | [
"jondurbin/airoboros-2.2",
"Open-Orca/OpenOrca",
"garage-bAInd/Open-Platypus",
"WizardLM/WizardLM_evol_instruct_V2_196k",
"TokenBender/python_eval_instruct_51k"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
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"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"BertNormalizer"
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"BertPreTokenizer"
] | [
"WordPiece"
] | 760 | AMR-KELEG/Sentence-ALDi | AMR-KELEG | null | 4,225 | 238,261 | False | 2023-10-05T09:19:17Z | 2025-07-19T13:36:09Z | transformers | 3 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"optimizer.pt",
"pytorch_model.bin",
"rng_state.pth",
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"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json",
"training_args.bin",
"vocab.txt"
] | d8ce98a134cc21bfa38977480ebf56fca49276ab | [
"transformers",
"pytorch",
"bert",
"text-classification",
"text-embeddings-inference",
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] | 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",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "inference": false} | null | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
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] | [
"text-classification"
] | [
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"logits"
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651c0cf69571da71a4dcd10e | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | RedHatAI/bge-base-en-v1.5-quant | RedHatAI | null | 424 | 180,843 | False | 2023-10-03T12:45:42Z | 2023-11-13T17:04:42Z | transformers | 4 | 0 | [{"name": "bge-base-en-v1.5-quant", "results": [{"task": {"type": "Classification"}, "dataset": {"type": "mteb/amazon_counterfactual", "name": "MTEB AmazonCounterfactualClassification (en)", "config": "en", "split": "test", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205"}, "metrics": [{"type": "accuracy", "value... | feature-extraction | null | [
".gitattributes",
"README.md",
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] | f890007506a96f95c1ac47118d65a4189021d967 | [
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"deepsparse",
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"license:mit",
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] | null | {"architectures": ["BertModel"], "model_type": "bert"} | {
"auto_model": "AutoModel",
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"pipeline_tag": "feature-extraction",
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} | {"language": ["en"], "license": "mit", "tags": ["mteb", "sparse", "sparsity", "quantized", "onnx", "embeddings", "int8", "deepsparse"], "model-index": [{"name": "bge-base-en-v1.5-quant", "results": [{"task": {"type": "Classification"}, "dataset": {"name": "MTEB AmazonCounterfactualClassification (en)", "type": "mteb/am... | null | null | [
"mit"
] | null | [
"en"
] | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
66cd158cd688c0c8873cc570 | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | gokaygokay/Flux-Prompt-Enhance | gokaygokay | {
"models": [
{
"_id": "621ffdc036468d709f174356",
"id": "google-t5/t5-base"
}
],
"relation": "finetune"
} | 18,082 | 201,230 | False | 2024-08-26T23:53:48Z | 2024-09-18T01:48:22Z | transformers | 64 | 0 | null | text-generation | {"parameters": {"F32": 222903552}, "total": 222903552} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | c7b01bb716a6124ab491c2ec327f9a2eff213937 | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"en",
"dataset:gokaygokay/prompt-enhancer-dataset",
"base_model:google-t5/t5-base",
"base_model:finetune:google-t5/t5-base",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "google-t5/t5-base", "datasets": ["gokaygokay/prompt-enhancer-dataset"], "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": "text2text-generation", "tags": null... | ```python
from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
device = "cuda" if torch.cuda.is_available() else "cpu"
# Model checkpoint
model_checkpoint = "gokaygokay/Flux-Prompt-Enhance"
# Tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
# Model
model = AutoModelForSeq2Seq... | null | [
"apache-2.0"
] | [
"gokaygokay/prompt-enhancer-dataset"
] | [
"en"
] | 222,903,552 | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17ae9b | 336c2005a03d2a38 | f74d2fa1431f2349 | 256,008 | Unigram | null | true | true | true | true | 11 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 415 | facebook/xglm-4.5B | facebook | null | 1,149 | 185,624 | False | 2022-03-02T23:29:05Z | 2023-09-07T15:10:11Z | transformers | 20 | 0 | null | text-generation | {"parameters": {"F16": 5076815872}, "total": 5076815872} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 1c2905c6ab3ea065e09e61daa12e3af0d246ca7e | [
"transformers",
"pytorch",
"safetensors",
"xglm",
"text-generation",
"multilingual",
"en",
"ru",
"zh",
"de",
"es",
"fr",
"ja",
"it",
"pt",
"el",
"ko",
"fi",
"id",
"tr",
"ar",
"vi",
"th",
"bg",
"ca",
"hi",
"et",
"bn",
"ta",
"ur",
"sw",
"te",
"eu",
"my... | null | {"architectures": ["XGLMForCausalLM"], "model_type": "xglm", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["multilingual", "en", "ru", "zh", "de", "es", "fr", "ja", "it", "pt", "el", "ko", "fi", "id", "tr", "ar", "vi", "th", "bg", "ca", "hi", "et", "bn", "ta", "ur", "sw", "te", "eu", "my", "ht", "qu"], "library_name": null, "license": "mit", "license_... | # XGLM-4.5B
XGLM-4.5B is a multilingual autoregressive language model (with 4.5 billion parameters) trained on a balanced corpus of a diverse set of 134 languages. It was introduced in the paper [Few-shot Learning with Multilingual Language Models](https://arxiv.org/abs/2112.10668) by Xi Victoria Lin\*, Todor Mihaylov... | null | [
"mit"
] | null | [
"multilingual",
"en",
"ru",
"zh",
"de",
"es",
"fr",
"ja",
"it",
"pt",
"el",
"ko",
"fi",
"id",
"tr",
"ar",
"vi",
"th",
"bg",
"ca",
"hi",
"et",
"bn",
"ta",
"ur",
"sw",
"te",
"eu",
"my",
"ht",
"qu"
] | 5,076,815,872 | null | null | [
"AutoModelForCausalLM",
"xglm",
"XGLMForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68221bc1ca0ef183d5746082 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | Intelligent-Internet/II-Medical-8B | Intelligent-Internet | null | 1,459 | 185,426 | False | 2025-05-12T16:03:13Z | 2025-08-12T07:48:17Z | transformers | 204 | 0 | null | text-generation | {"parameters": {"BF16": 8190735360}, "total": 8190735360} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_to... | 545fa0238261e041fb1ef3f6ed644a5a8f8400e3 | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"arxiv:2503.19633",
"arxiv:2503.10460",
"arxiv:2501.19393",
"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 not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{ '<|im_start|>' + message['role'] + '\n' + message['content'] | trim + '<... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # II-Medical-8B
<div style="display: flex; justify-content: center;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6389496ff7d3b0df092095ed/73Y-oDmehp0eJ2HWrfn3V.jpeg" width="800">
</div>
## I. Model Overview
II-Medical-8B is the newest advanced large language model developed by Intelligent In... | null | [
"apache-2.0"
] | null | null | 8,190,735,360 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6659fbea458a2f52c400bca4 | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | echarlaix/tiny-random-t5 | echarlaix | null | 8,963 | 222,622 | False | 2024-05-31T16:33:46Z | 2024-05-31T16:35:01Z | transformers | 0 | 0 | null | feature-extraction | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json"
] | 655b12286719592ac60ea875f909f628fec34806 | [
"transformers",
"pytorch",
"tf",
"t5",
"feature-extraction",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5Model"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | [
"apache-2.0"
] | null | null | null | null | null | [
"t5",
"T5Model",
"AutoModel"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] | |
648999c7ee39dded816b750a | d12c4550c74b522a | 749336c707479b60 | 49,153 | BPE | 48,891 | false | true | false | true | 20 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 451 | WizardLMTeam/WizardCoder-15B-V1.0 | WizardLMTeam | null | 293 | 175,840 | False | 2023-06-14T10:43:19Z | 2024-01-19T03:06:36Z | transformers | 763 | 0 | [{"name": "WizardCoder", "results": [{"task": {"type": "text-generation"}, "dataset": {"type": "openai_humaneval", "name": "HumanEval"}, "metrics": [{"name": "pass@1", "type": "pass@1", "value": 0.573, "verified": false}]}]}] | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 9c177589dec389eac2c8de51cbc371d45e47984e | [
"transformers",
"pytorch",
"gpt_bigcode",
"text-generation",
"code",
"arxiv:2304.12244",
"arxiv:2306.08568",
"arxiv:2308.09583",
"license:bigscience-openrail-m",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTBigCodeForCausalLM"], "model_type": "gpt_bigcode", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"library_name": "transformers", "license": "bigscience-openrail-m", "metrics": ["code_eval"], "tags": ["code"], "model-index": [{"name": "WizardCoder", "results": [{"task": {"type": "text-generation"}, "dataset": {"name": "HumanEval", "type": "openai_humaneval"}, "metrics": [{"type": "pass@1", "value": 0.573, "name": ... | ## WizardCoder: Empowering Code Large Language Models with Evol-Instruct
<p style="font-size:28px;" align="center">
🏠 <a href="https://wizardlm.github.io/" target="_blank">Home Page</a> </p>
<p align="center">
<p align="center">
🤗 <a href="https://huggingface.co/WizardLM" target="_blank">HF Repo</a> •🐱 <a href="ht... | null | [
"bigscience-openrail-m"
] | null | null | null | null | [
"code_eval"
] | [
"gpt_bigcode",
"AutoModelForCausalLM",
"GPTBigCodeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6621de5c761807483a5230a6 | 336c4bf4be7d271a | 87995784a2525d28 | 32,005 | BPE | 61,249 | true | false | true | true | 8 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 761 | instructlab/granite-7b-lab | instructlab | {
"models": [
{
"_id": "66229dfe8b4f9558fc466d31",
"id": "ibm-granite/granite-7b-base"
}
],
"relation": "finetune"
} | 518 | 180,002 | False | 2024-04-19T03:00:44Z | 2024-06-05T21:13:24Z | transformers | 43 | 0 | null | text-generation | {"parameters": {"BF16": 6738481152}, "total": 6738481152} | [
".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-card/Model Card for Merlinite 7b 28cc0b72cf574a4a828140d3539ede4a_Screenshot_2024-02-22_at_1... | 4fb6a018d68ab813b95c7f470e424a70f2f7e561 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"granite",
"ibm",
"lab",
"labrador",
"labradorite",
"conversational",
"en",
"arxiv:2403.01081",
"base_model:ibm-granite/granite-7b-base",
"base_model:finetune:ibm-granite/granite-7b-base",
"license:apache-2.0",
"text-generation... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>'+ '\n' + message['content'] + '\n'}}{% elif message['role'] == 'user' %}{{'<|user|>' + '\n' + message['content'] + '\n'... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "ibm/granite-7b-base", "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": "text-generation", "tags": ["granite", "ibm", "lab", "labrador", "labradorite"... | # Model Card for Granite-7b-lab [Paper](https://arxiv.org/abs/2403.01081)
### Overview
### Performance
| Model | Alignment | Base | Teacher | MTBen... | null | [
"apache-2.0"
] | null | [
"en"
] | 6,738,481,152 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67bda7564d1a6d38f8189107 | 7c2a837aac87574b | 1e78464774d502ca | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 762 | EuroBERT/EuroBERT-610m | EuroBERT | null | 1,588 | 184,691 | False | 2025-02-25T11:19:50Z | 2025-10-18T16:22:14Z | transformers | 33 | 0 | null | fill-mask | {"parameters": {"F32": 755625600}, "total": 755625600} | [
".gitattributes",
"README.md",
"config.json",
"configuration_eurobert.py",
"img/banner.png",
"img/code_math.png",
"img/long_context.png",
"img/multilingual.png",
"model.safetensors",
"modeling_eurobert.py",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config... | d9af784ed20db6c2096e335ec6a67dd4a219924c | [
"transformers",
"pytorch",
"safetensors",
"eurobert",
"fill-mask",
"code",
"custom_code",
"en",
"fr",
"de",
"es",
"zh",
"it",
"ru",
"pl",
"pt",
"ja",
"vi",
"nl",
"ar",
"tr",
"hi",
"arxiv:2503.05500",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["EuroBertForMaskedLM"], "auto_map": {"AutoConfig": "configuration_eurobert.EuroBertConfig", "AutoModel": "modeling_eurobert.EuroBertModel", "AutoModelForPreTraining": "modeling_eurobert.EuroBertPreTrainedModel", "AutoModelForMaskedLM": "modeling_eurobert.EuroBertForMaskedLM", "AutoModelForSequenceCla... | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "fr", "de", "es", "zh", "it", "ru", "pl", "pt", "ja", "vi", "nl", "ar", "tr", "hi"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "... | # EuroBERT-610m
<div>
<img src="img/banner.png" width="100%" alt="EuroBERT" />
</div>
## Table of Contents
1. [Overview](#overview)
2. [Usage](#Usage)
3. [Evaluation](#Evaluation)
4. [License](#license)
5. [Citation](#citation)
## Overview
EuroBERT is a family of multilingual encoder models designed for a variety... | null | [
"apache-2.0"
] | null | [
"en",
"fr",
"de",
"es",
"zh",
"it",
"ru",
"pl",
"pt",
"ja",
"vi",
"nl",
"ar",
"tr",
"hi"
] | 755,625,600 | null | null | [
"EuroBertForMaskedLM",
"AutoModelForMaskedLM",
"eurobert"
] | [
"fill-mask"
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"text"
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"text"
] | [
"logits"
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | OPI-PG/Qra-7b | OPI-PG | null | 1,362 | 175,840 | False | 2024-02-27T06:05:26Z | 2024-03-16T11:06:32Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"BF16": 6738415616}, "total": 6738415616} | [
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"safetensors",
"llama",
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"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "</s>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
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Qra is a series of LLMs adapted to the Polish language, resulting from a collaboration between the National Information Processing Institute (OPI) and Gdańsk University of Technology (PG). The models were trained o... | null | [
"llama2"
] | null | null | 6,738,415,616 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67db552c3340510c64afbe58 | d9abafc9e84f6e37 | 298fb2136b26cee9 | 131,072 | BPE | 269,443 | false | true | true | true | 1,000 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 482 | nvidia/Nemotron-H-8B-Base-8K | nvidia | null | 30,881 | 252,904 | False | 2025-03-19T23:37:16Z | 2025-08-21T15:45:04Z | transformers | 55 | 0 | null | text-generation | {"parameters": {"BF16": 8100852736}, "total": 8100852736} | [
".gitattributes",
"README.md",
"config.json",
"configuration_nemotron_h.py",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"modeling_nemotro... | 94ea861e008c2dfced3e8e1302094024077aa04e | [
"transformers",
"safetensors",
"nvidia",
"pytorch",
"nemotron-h",
"text-generation",
"conversational",
"en",
"de",
"es",
"fr",
"it",
"ko",
"pt",
"ru",
"jp",
"zh",
"arxiv:2504.03624",
"license:other",
"endpoints_compatible",
"region:us"
] | null | {"tokenizer_config": {"bos_token": "<s>", "chat_template": "{{'<SPECIAL_10>System'}}{% for message in messages %}{% if message['role'] == 'system' %}{{'\n' + message['content'].strip()}}{% endif %}{% endfor %}{{'\n'}}{% for message in messages %}{% if message['role'] == 'user' %}{{ '\n<SPECIAL_11>User\n' + message['con... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "de", "es", "fr", "it", "ko", "pt", "ru", "jp", "zh"], "library_name": "transformers", "license": "other", "license_name": "nvidia-internal-scientific-research-and-development-model-license", "license_link": "https://www.nvidia.com/en-us/ag... | # Nemotron-H-8B-Base-8K
## Model Overview
NVIDIA Nemotron-H-8B-Base-8K is a large language model (LLM) developed by NVIDIA that is designed as a completion model for a given piece of text. It uses a hybrid model architecture that consists primarily of Mamba-2 and MLP layers combined with just four Attention layers. ... | null | [
"other",
"nvidia-internal-scientific-research-and-development-model-license",
"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-internal-scientific-research-and-development-model-license/"
] | null | [
"en",
"de",
"es",
"fr",
"it",
"ko",
"pt",
"ru",
"jp",
"zh"
] | 8,100,852,736 | null | null | [
"AutoModel"
] | [
null,
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
665ecc2e04fd28c09c5ba355 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/Qwen2-57B-A14B-Instruct | Qwen | {
"models": [
{
"_id": "664e3495e4de44dd2836d3f5",
"id": "Qwen/Qwen2-57B-A14B"
}
],
"relation": "finetune"
} | 14,843 | 236,954 | False | 2024-06-04T08:11:26Z | 2024-08-21T10:24:04Z | transformers | 83 | 0 | null | text-generation | {"parameters": {"BF16": 57408658944}, "total": 57408658944} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
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"model-00004-of-00029.safetensors",
"model-00005-of-00029.safetensors",
"model-00006-of-0... | 50896d66b39f1425d63720541a66c7df13e053c0 | [
"transformers",
"safetensors",
"qwen2_moe",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2309.00071",
"base_model:Qwen/Qwen2-57B-A14B",
"base_model:finetune:Qwen/Qwen2-57B-A14B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen2MoeForCausalLM"], "model_type": "qwen2_moe", "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['r... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-57B-A14B", "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": "text-generation", "tags": ["chat"]} | # Qwen2-57B-A14B-Instruct
## Introduction
Qwen2 is the new series of Qwen large language models. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the instruction-tuned 57B-A1... | null | [
"apache-2.0"
] | null | [
"en"
] | 57,408,658,944 | null | null | [
"qwen2_moe",
"AutoModelForCausalLM",
"Qwen2MoeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6249feb4d9520873d3a0b0eb | 62b0d28ff93ceae2 | 715f7a5962d8b04a | 50,265 | BPE | 50,004 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 763 | somosnlp-hackathon-2022/readability-es-3class-paragraphs | somosnlp-hackathon-2022 | null | 284 | 173,088 | False | 2022-04-03T20:08:20Z | 2023-04-13T08:45:37Z | transformers | 1 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 124647939}, "total": 124648453} | [
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"tokenizer_config.json",
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] | 278cdd7eda10e2fd0e6f207f426dee8bbf028077 | [
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"safetensors",
"roberta",
"text-classification",
"spanish",
"bertin",
"es",
"license:cc-by-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "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": "es", "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": ["spanish", "roberta", "bertin"], "widget": [{"text": "Las L\u00edn... | # Readability ES Paragraphs for three classes
Model based on the Roberta architecture finetuned on [BERTIN](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) for readability assessment of Spanish texts.
## Description and performance
This version of the model was trained on a mix of datasets, using ... | null | [
"cc-by-4.0"
] | null | [
"es"
] | 124,648,453 | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f178f36 | dd8ef53ef5a0f56a | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 90 | amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061 | amansolanki | null | 64,102 | 235,759 | False | 2022-03-02T23:29:05Z | 2021-10-17T00:32:35Z | transformers | 0 | 0 | null | text-classification | null | [
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"pytorch_model.bin",
"sample_input.pkl",
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] | 7e66c09a995a61e7f37d29d72e064383ff7ca13e | [
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] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "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"
} | {"base_model": null, "datasets": ["amansolanki/autonlp-data-Tweet-Sentiment-Extraction"], "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": "I love AutoNL... | # Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 20114061
- CO2 Emissions (in grams): 3.651199395353127
## Validation Metrics
- Loss: 0.5046541690826416
- Accuracy: 0.8036219581211093
- Macro F1: 0.807095210403678
- Micro F1: 0.8036219581211093
- Weighted F1: 0.8039634739225368
- ... | null | null | [
"amansolanki/autonlp-data-Tweet-Sentiment-Extraction"
] | [
"en"
] | null | null | null | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
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] |
65f938e1b49d94e09404ff69 | 0037b4f3453f3382 | d1e0dcc971dc8303 | 32,002 | BPE | 58,980 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 764 | Nexusflow/Starling-LM-7B-beta | Nexusflow | null | 2,769 | 180,939 | False | 2024-03-19T07:04:01Z | 2024-04-03T21:30:33Z | transformers | 343 | 0 | null | text-generation | {"parameters": {"BF16": 7241748480}, "total": 7241748480} | [
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"RLHF",
"RLAIF",
"conversational",
"en",
"dataset:berkeley-nest/Nectar",
"arxiv:1909.08593",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{ bos_token }}{% for message in messages %}{{ 'GPT4 Correct ' + message['role'].title() + ': ' + message['content'] + '<|end_of_turn|>'}}{% endfor %}{% if add_generation_prompt %}{{ 'GPT4 Corre... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["berkeley-nest/Nectar"], "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": ["reward model", "RLHF", "RLAIF"]} | # Starling-LM-7B-beta
<!-- Provide a quick summary of what the model is/does. -->
- **Developed by: The Nexusflow Team (** Banghua Zhu * , Evan Frick * , Tianhao Wu * , Hanlin Zhu, Karthik Ganesan, Wei-Lin Chiang, Jian Zhang, and Jiantao Jiao).
- **Model type:** Language Model finetuned with RLHF / RLAIF
- **License:... | null | [
"apache-2.0"
] | [
"berkeley-nest/Nectar"
] | [
"en"
] | 7,241,748,480 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66cb5c05e51ba300920a7d71 | 35f8a93a304f6b78 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 6 | gokaygokay/Florence-2-Flux-Large | gokaygokay | {
"models": [
{
"_id": "666ce1af091b7c8e3f9aae7d",
"id": "microsoft/Florence-2-large"
}
],
"relation": "finetune"
} | 3,925 | 191,063 | False | 2024-08-25T16:29:57Z | 2024-09-18T01:48:49Z | transformers | 56 | 0 | null | image-text-to-text | {"parameters": {"F32": 822949977}, "total": 822949977} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_florence2.py",
"generation_config.json",
"merges.txt",
"model.safetensors",
"modeling_florence2.py",
"preprocessor_config.json",
"processing_florence2.py",
"special_tokens_map.json",
"tokenizer.json",
"tokeni... | ed3af3df6d23d9f25d1dd4ce05ba95bb43c37209 | [
"transformers",
"safetensors",
"florence2",
"image-text-to-text",
"art",
"custom_code",
"en",
"dataset:kadirnar/fluxdev_controlnet_16k",
"base_model:microsoft/Florence-2-large",
"base_model:finetune:microsoft/Florence-2-large",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Florence2ForConditionalGeneration"], "auto_map": {"AutoConfig": "configuration_florence2.Florence2Config", "AutoModelForCausalLM": "modeling_florence2.Florence2ForConditionalGeneration"}, "model_type": "florence2", "tokenizer_config": {}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": "microsoft/Florence-2-large", "datasets": ["kadirnar/fluxdev_controlnet_16k"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ... | ```
pip install -q datasets flash_attn timm einops
```
```python
from transformers import AutoModelForCausalLM, AutoProcessor, AutoConfig
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = AutoModelForCausalLM.from_pretrained("gokaygokay/Florence-2-Flux-Large", trust_remote_c... | null | [
"apache-2.0"
] | [
"kadirnar/fluxdev_controlnet_16k"
] | [
"en"
] | 822,949,977 | null | null | [
"florence2",
"AutoModelForImageTextToText",
"Florence2ForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
66a7a6ed5baa33fe01c27c87 | 7679cd48bb106d89 | ebd7f7bf136c21b9 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 362 | NousResearch/Hermes-3-Llama-3.1-70B | NousResearch | {
"models": [
{
"_id": "66944fd095c7fa6e68c314ae",
"id": "meta-llama/Llama-3.1-70B"
}
],
"relation": "finetune"
} | 799 | 176,764 | False | 2024-07-29T14:27:57Z | 2024-09-08T07:51:00Z | transformers | 122 | 0 | [{"name": "Hermes-3-Llama-3.1-70B", "results": []}] | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00030.safetensors",
"model-00002-of-00030.safetensors",
"model-00003-of-00030.safetensors",
"model-00004-of-00030.safetensors",
"model-00005-of-00030.safetensors",
"model-00006-of-00030.safetensors",
"model-0... | 1fc86da0ce9cdb14cd775ad270bc7d1b4bf70ede | [
"transformers",
"safetensors",
"llama",
"text-generation",
"Llama-3",
"instruct",
"finetune",
"chatml",
"gpt4",
"synthetic data",
"distillation",
"function calling",
"json mode",
"axolotl",
"roleplaying",
"chat",
"conversational",
"en",
"arxiv:2408.11857",
"base_model:meta-llam... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": [{"name": "default", "template": "{{bos_token}}{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Meta-Llama-3.1-70B", "datasets": null, "eval_results": [], "language": ["en"], "library_name": null, "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": "Hermes-3-Llama-3.1-70B", "pipeline_tag": null, "tags": ["Llama-3", "instruct", "finetune", "cha... | # Hermes 3 - Llama-3.1 70B
## Model Description
Hermes 3 is the latest version of our flagship Hermes series of LLMs by Nous Research.
For more details on new capabilities, training results, and... | null | [
"llama3"
] | null | [
"en"
] | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
62c52c5d1b164ce196f83880 | 97ddb05b02dc5a05 | 384eeeb35a4474b1 | 32,100 | BPE | 31,739 | false | true | true | true | 105 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 644 | Salesforce/codet5-large-ntp-py | Salesforce | null | 367 | 172,056 | False | 2022-07-06T06:31:57Z | 2025-01-21T09:32:14Z | transformers | 27 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | bb9847dbad3ef28de5bfbca79f3ff613f4c65565 | [
"transformers",
"pytorch",
"t5",
"text-generation",
"arxiv:2109.00859",
"arxiv:2207.01780",
"arxiv:1909.09436",
"license:bsd-3-clause",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5WithLMHeadModel"], "model_type": "t5", "tokenizer_config": {"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": tr... | {
"auto_model": "AutoModelWithLMHead",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "bsd-3-clause", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # CodeT5 (large-size model pretrained with NTP objective on Python)
## Model description
CodeT5 is a family of encoder-decoder language models for code from the paper: [CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation](https://arxiv.org/pdf/2109.00859.pdf) by Y... | null | [
"bsd-3-clause"
] | null | null | null | null | null | [
"t5",
"T5WithLMHeadModel",
"AutoModelWithLMHead"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
658b5d8a674aa14b9bf35d58 | 30e323b30348e1e3 | b927f436c0f7aef5 | 128,000 | WordPiece | null | true | true | true | false | 6 | Sequence | Split | null | [
"NFD",
"Lowercase",
"StripAccents",
"Replace",
"Replace"
] | [
"Split"
] | null | 765 | dicta-il/dictabert-ner | dicta-il | null | 820 | 174,895 | False | 2023-12-26T23:11:06Z | 2024-01-01T00:42:24Z | transformers | 6 | 0 | null | token-classification | {"parameters": {"F32": 183775515}, "total": 183775515} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 05ed61bc99437b13bc2bdef8154c52f8b44eaad6 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"he",
"arxiv:2308.16687",
"license:cc-by-4.0",
"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": ["he"], "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew
State-of-the-art language model for Hebrew, released [here](https://arxiv.org/abs/2308.16687).
This is the fine-tuned BERT-base model for the named-entity-recognition task.
For the bert-base models for other tasks, see [here](https://huggingface.co/collect... | null | [
"cc-by-4.0"
] | null | [
"he"
] | 183,775,515 | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66062fcf04b9742480db7483 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | LnL-AI/TinyLlama-1.1B-Chat-v1.0-GPTQ-4bit | LnL-AI | null | 19,131 | 229,094 | False | 2024-03-29T03:04:47Z | 2024-06-26T05:37:37Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"gptq_model-4bit-128g.safetensors",
"quantize_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | ded624dfe07a12f49ebb3b1a183f43d86f178b62 | [
"transformers",
"llama",
"text-generation",
"conversational",
"license:unknown",
"endpoints_compatible",
"4-bit",
"gptq",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "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['r... | {
"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": "unknown", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | This is TinyLlama/TinyLlama-1.1B-Chat-v1.0 quantized with AutoGPTQ in GPTQ 4-bit format.
**Quantize config:**
```
{
"bits": 4,
"group_size": 128,
"damp_percent": 0.01,
"desc_act": false,
"static_groups": false,
"sym": true,
"true_sequential": true,
"model_name_or_path": null,
"model_file_base_nam... | null | [
"unknown"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66314b18a2354b0f509b5949 | 39b1e434a495263c | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 349 | shanchen/llama3-8B-slerp-med-chinese | shanchen | {
"models": [
{
"_id": "66293358292184d586b783c1",
"id": "johnsnowlabs/JSL-MedLlama-3-8B-v1.0"
},
{
"_id": "6627492e0601587f0be631ea",
"id": "winninghealth/WiNGPT2-Llama-3-8B-Base"
}
],
"relation": "merge"
} | 9,141 | 214,867 | False | 2024-04-30T19:48:40Z | 2024-04-30T20:01:48Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"config.json",
"mergekit_config.yml",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | f234f794019d98ace332115134997ba4224d8883 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"winninghealth/WiNGPT2-Llama-3-8B-Base",
"johnsnowlabs/JSL-MedLlama-3-8B-v1.0",
"zh",
"en",
"fr",
"base_model:johnsnowlabs/JSL-MedLlama-3-8B-v1.0",
"base_model:merge:johnsnowlabs/JSL-MedLlama-3-... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|end_of_text|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["winninghealth/WiNGPT2-Llama-3-8B-Base", "johnsnowlabs/JSL-MedLlama-3-8B-v1.0"], "datasets": null, "eval_results": null, "language": ["zh", "en", "fr"], "library_name": null, "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags... | # llama3-8B-slerp-med-chinese
llama3-8B-slerp-med-chinese is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [winninghealth/WiNGPT2-Llama-3-8B-Base](https://huggingface.co/winninghealth/WiNGPT2-Llama-3-8B-Base)
* [johnsnowla... | null | [
"llama3"
] | null | [
"zh",
"en",
"fr"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
679ca1f8829e41ce4a9cd3d8 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | unsloth/Qwen2.5-VL-3B-Instruct-unsloth-bnb-4bit | unsloth | {
"models": [
{
"_id": "6795ff8f7534713f94918fc5",
"id": "Qwen/Qwen2.5-VL-3B-Instruct"
}
],
"relation": "quantized"
} | 8,609 | 211,029 | False | 2025-01-31T10:12:08Z | 2025-05-12T08:58:18Z | transformers | 14 | 0 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"chat_template.json",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"preprocessor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | bf02647c86e6cd6be615d9982acab6c8bd82bffc | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"multimodal",
"unsloth",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-VL-3B-Instruct",
"text-generation-inf... | null | {"architectures": ["Qwen2_5_VLForConditionalGeneration"], "model_type": "qwen2_5_vl", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "processor_config": {"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for me... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["Qwen/Qwen2.5-VL-3B-Instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": null, "license_name": "qwen-research", "license_link": "https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, "pipe... | # Qwen2.5-VL-3B-Instruct
<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Introduction
In the past five months since Qwen2-VL’s r... | null | [
"qwen-research",
"https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct/blob/main/LICENSE"
] | null | [
"en"
] | null | null | null | [
"qwen2_5_vl",
"AutoModelForImageTextToText",
"Qwen2_5_VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
669fd707161a21fef9ad18d4 | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | unsloth/Meta-Llama-3.1-70B-bnb-4bit | unsloth | {
"models": [
{
"_id": "66944fd095c7fa6e68c314ae",
"id": "meta-llama/Llama-3.1-70B"
}
],
"relation": "quantized"
} | 5,986 | 189,879 | False | 2024-07-23T16:15:03Z | 2024-11-22T07:26:25Z | transformers | 32 | 0 | null | text-generation | {"parameters": {"F32": 4330240, "BF16": 2102665216, "U8": 70590329766}, "total": 72697325222} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00006.safetensors",
"model-00002-of-00006.safetensors",
"model-00003-of-00006.safetensors",
"model-00004-of-00006.safetensors",
"model-00005-of-00006.safetensors",
"model-00006-of-00006.safetensors",
"model.s... | a009b8db2439814febe725486a5ed388f12a8744 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-3",
"meta",
"facebook",
"unsloth",
"en",
"base_model:meta-llama/Llama-3.1-70B",
"base_model:quantized:meta-llama/Llama-3.1-70B",
"license:llama3.1",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandb... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|end_of_text|>", "pad_token": "<|finetune_right_pad_id|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Llama-3.1-70B", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "llama3.1", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["llama-3", "llama", "meta", "facebook", "unsloth",... | # Finetune Llama 3.1, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here: https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/D... | null | [
"llama3.1"
] | null | [
"en"
] | 72,697,325,222 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
682ad9e695b2dde84376f69a | b7aceb3003302d0b | 052c2f25c450ea19 | 73,921 | BPE | 49,721 | true | true | true | true | 23,944 | NFKC | Sequence | ByteLevel | [
"NFKC"
] | [
"Split",
"Digits",
"Split",
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 766 | ByteDance/Dolphin | ByteDance | null | 980 | 183,408 | False | 2025-05-19T07:12:38Z | 2025-07-16T11:58:36Z | transformers | 515 | 0 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"preprocessor_config.json",
"special_tokens_map.json",
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] | 0ff4b22d8c00b20750cdba75cfe1336bd603b249 | [
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"ocr",
"layout-analysis",
"table-extraction",
"multimodal",
"vision-language-model",
"zh",
"en",
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"license:mit",
"end... | null | {"architectures": ["VisionEncoderDecoderModel"], "model_type": "vision-encoder-decoder", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["custom"], "eval_results": null, "language": ["zh", "en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ["document-parsing", "document-understanding", "do... | null | null | [
"mit"
] | [
"custom"
] | [
"zh",
"en"
] | null | null | null | [
"AutoModelForImageTextToText",
"vision-encoder-decoder",
"VisionEncoderDecoderModel"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
642fb9643728df73af5300b8 | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | ToddGoldfarb/Cadet-Tiny | ToddGoldfarb | null | 111 | 175,315 | False | 2023-04-07T06:34:12Z | 2023-05-12T00:18:41Z | transformers | 6 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | 04d1210ca2c58b89ea8d278298e2725450466991 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"conversational",
"en",
"dataset:allenai/soda",
"license:openrail",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["allenai/soda"], "eval_results": null, "language": ["en"], "library_name": null, "license": "openrail", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "conversational", "tags": null} | # What is Cadet-Tiny?
Inspired by Allen AI's **Cosmo-XL**, **Cadet-Tiny** is a _very small_ conversational model trained off of the **SODA** dataset. **Cadet-Tiny** is intended for inference at the edge (on something as small as a 2GB RAM Raspberry Pi).
**Cadet-Tiny** is trained off of the **t5-small** pretrained mod... | null | [
"openrail"
] | [
"allenai/soda"
] | [
"en"
] | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1803c2 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | sgugger/tiny-distilbert-classification | sgugger | null | 1,140 | 172,756 | False | 2022-03-02T23:29:05Z | 2021-07-29T17:12:02Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | a30e0f7dc9dc24b0dacce98fd144e0a7ffb70a1a | [
"transformers",
"pytorch",
"tf",
"distilbert",
"text-classification",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "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 | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66615487a4c55c16aceb4423 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/Qwen2-1.5B-Instruct-AWQ | Qwen | {
"models": [
{
"_id": "665d87fc0f43f1c4ad1ce2a1",
"id": "Qwen/Qwen2-1.5B-Instruct"
}
],
"relation": "quantized"
} | 21,042 | 246,009 | False | 2024-06-06T06:17:43Z | 2024-08-21T10:35:28Z | transformers | 9 | 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"
] | 688a0bab90cef22c0a5fad44dbda2b65a8859147 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"base_model:Qwen/Qwen2-1.5B-Instruct",
"base_model:quantized:Qwen/Qwen2-1.5B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"awq",
"deploy:azure",
... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-1.5B-Instruct", "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": "text-generation", "tags": ["chat"]} | # Qwen2-1.5B-Instruct-AWQ
## Introduction
Qwen2 is the new series of Qwen large language models. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the instruction-tuned 1.5B Q... | null | [
"apache-2.0"
] | null | [
"en"
] | 1,777,088,000 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63d0aae51723379b77816bcc | 2012b52fa41ec860 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 113 | heegyu/gpt2-emotion | heegyu | null | 14 | 171,208 | False | 2023-01-25T04:07:01Z | 2023-03-19T08:03:17Z | transformers | 2 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json",
"training_args.bin",
"vocab.json"
] | 5acffad36ea9ec33800e2f92c378214e48f37ce6 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"en",
"dataset:emotion",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"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": ["emotion"], "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": null} | - **Developed by:** Heegyu Kim
- **Model type:** GPT-2
- **Language(s) (NLP):** English
- **License:** MIT
# Uses
```
from transformers import pipeline
generator = pipeline('text-generation', 'heegyu/gpt2-emotion')
prompt = "sadness I'm so " # start token should be one of ["sadness", "joy", "love", "anger", "fear",... | null | [
"mit"
] | [
"emotion"
] | [
"en"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
687c61b066d1fc7f73788fc2 | 0fbdb3abe17d0d5f | b02c1908f37c4055 | 151,365 | BPE | 318,088 | false | true | true | true | 36 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 320 | zai-org/GLM-4.5 | zai-org | null | 65,227 | 347,968 | False | 2025-07-20T03:25:36Z | 2025-08-11T13:27:03Z | transformers | 1,397 | 1 | null | text-generation | {"parameters": {"BF16": 358337776896, "F32": 14400}, "total": 358337791296} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model-00001-of-00093.safetensors",
"model-00002-of-00093.safetensors",
"model-00003-of-00093.safetensors",
"model-00004-of-00093.safetensors",
"model-00005-of-00093.safetensors",
"model-00006-of-00093... | cbb2c7cfb52fa128a9660cb1a7a78e017899e115 | [
"transformers",
"safetensors",
"glm4_moe",
"text-generation",
"conversational",
"en",
"zh",
"arxiv:2508.06471",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Glm4MoeForCausalLM"], "model_type": "glm4_moe", "tokenizer_config": {"eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}, "chat_template_jinja": "[gMASK]<sop>\n{%- if tools -%}\n<|system|>\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "zh"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | # GLM-4.5
<div align="center">
<img src=https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg width="15%"/>
</div>
<p align="center">
👋 Join our <a href="https://discord.gg/QR7SARHRxK" target="_blank">Discord</a> community.
<br>
📖 Check out the GLM-4.5 <a href="https://z.ai... | null | [
"mit"
] | null | [
"en",
"zh"
] | 358,337,791,296 | null | null | [
"AutoModelForCausalLM",
"Glm4MoeForCausalLM",
"glm4_moe"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6469d3d7f51b56a285b90529 | b9c4d5f4e9446fec | 851f4e82f0ea6be0 | 501,153 | WordPiece | null | true | true | true | true | 1 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 280 | setu4993/LEALLA-base | setu4993 | null | 8,357 | 181,129 | False | 2023-05-21T08:18:31Z | 2023-10-19T06:20:13Z | transformers | 5 | 0 | null | sentence-similarity | {"parameters": {"I64": 512, "F32": 107034240}, "total": 107034752} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 4372d1b5995482b7237381ea0c833c5c404856f2 | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"feature-extraction",
"sentence_embedding",
"multilingual",
"google",
"sentence-similarity",
"lealla",
"labse",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"bo",
"bs",
"ca",
"ceb",
"co",
"cs",
"c... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["CommonCrawl", "Wikipedia"], "eval_results": null, "language": ["af", "am", "ar", "as", "az", "be", "bg", "bn", "bo", "bs", "ca", "ceb", "co", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "haw", "he", "hi", "hmn", "hr... | # LEALLA-base
## Model description
LEALLA is a collection of lightweight language-agnostic sentence embedding models supporting 109 languages, distilled from [LaBSE](https://ai.googleblog.com/2020/08/language-agnostic-bert-sentence.html). The model is useful for getting multilingual sentence embeddings and for bi-tex... | null | [
"apache-2.0"
] | [
"CommonCrawl",
"Wikipedia"
] | [
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"bo",
"bs",
"ca",
"ceb",
"co",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha",
"haw",
"he",
"hi",
"hmn",
"hr",
"ht",
"hu",
"... | 107,034,752 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
65c391706a29bb7649dff708 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | Ttimofeyka/MistralRP-Noromaid-NSFW-Mistral-7B-GGUF | Ttimofeyka | null | 12,673 | 229,415 | False | 2024-02-07T14:19:28Z | 2024-02-10T11:41:00Z | transformers | 77 | 0 | null | text-generation | null | [
".gitattributes",
"MistralRP-Noromaid-NSFW-7B-Q4_0.gguf",
"MistralRP-Noromaid-NSFW-7B-Q5_K_M.gguf",
"MistralRP-Noromaid-NSFW-7B-Q8_0.gguf",
"README.md",
"config.json",
"mergekit_config.yml",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokeni... | dc414dd9e46fa0b2ca246c27f14ff2a98c243efe | [
"transformers",
"safetensors",
"gguf",
"mistral",
"text-generation",
"mergekit",
"merge",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | {"total": 7241732096, "architecture": "llama", "context_length": 32768, "bos_token": "<s>", "eos_token": "</s>"} | {"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",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": [], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["mergekit", "merge"]} | # Model
This is a merge model of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Model Details
### Prompt template: Alpaca
```
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Respons... | null | null | null | null | null | 7,241,732,096 | null | [
"AutoModelForCausalLM",
"llama",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17b5d2 | 69d9860d38b5c798 | cf7a052aa6fec7ad | 30,000 | BPE | 15,977 | true | true | false | true | 229 | Sequence | Metaspace | Metaspace | [
"NFKC",
"BertNormalizer"
] | [
"Metaspace"
] | [
"Metaspace"
] | 282 | gogamza/kobart-base-v1 | gogamza | null | 826 | 174,406 | False | 2022-03-02T23:29:05Z | 2023-06-29T00:45:30Z | transformers | 1 | 0 | null | feature-extraction | {"parameters": {"F32": 123859968}, "total": 123859968} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"vocab.json"
] | 5aa5969f3c0b5df5ab02be4f747bf3601c4fdb61 | [
"transformers",
"pytorch",
"safetensors",
"bart",
"feature-extraction",
"ko",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BartModel"], "model_type": "bart"} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "ko", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["bart"]} | ## KoBART-base-v1
```python
from transformers import PreTrainedTokenizerFast, BartModel
tokenizer = PreTrainedTokenizerFast.from_pretrained('gogamza/kobart-base-v1')
model = BartModel.from_pretrained('gogamza/kobart-base-v1')
``` | null | [
"mit"
] | null | [
"ko"
] | 123,859,968 | null | null | [
"AutoModel",
"bart",
"BartModel"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
66272cfe846c2a66a7b099a9 | 803e3c8528c55bf1 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 352 | FlagAlpha/Llama3-Chinese-8B-Instruct | FlagAlpha | null | 16,745 | 251,478 | False | 2024-04-23T03:37:34Z | 2024-04-24T02:33:43Z | transformers | 79 | 0 | null | text-generation | {"parameters": {"F16": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"config.json",
"configuration_llama.py",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"modeling_llama.py",
... | d76c4a5d365b041d1b440337dbf7da9664a464fc | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama3",
"chinese",
"conversational",
"custom_code",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "auto_map": {"AutoConfig": "configuration_llama.LlamaConfig", "AutoModel": "modeling_llama.LlamaForCausalLM", "AutoModelForCausalLM": "modeling_llama.LlamaForCausalLM", "AutoModelForSequenceClassification": "modeling_llama.LlamaForSequenceClassification"}, "model_type": "llama", ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["llama3", "chinese"]} | # Llama3-Chinese-8B-Instruct
Llama3-Chinese-8B-Instruct基于Llama3-8B中文微调对话模型，由Llama中文社区和AtomEcho（原子回声）联合研发，我们会持续提供更新的模型参数，模型训练过程见 [https://llama.family](https://llama.family)。
模型的部署、训练、微调等方法详见Llama中文社区GitHub仓库：[https://github.com/LlamaFamily/Llama-Chinese](https://github.com/LlamaFamily/Llama-Chinese)
## 如何使用
```
imp... | null | [
"apache-2.0"
] | null | null | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6898a4d2873aa6ebca0f8822 | 0fbdb3abe17d0d5f | b02c1908f37c4055 | 151,365 | BPE | 318,088 | false | true | true | true | 36 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 320 | zai-org/GLM-4.5V | zai-org | {
"models": [
{
"_id": "687c617b24649ecb26a74106",
"id": "zai-org/GLM-4.5-Air-Base"
}
],
"relation": "finetune"
} | 46,010 | 382,517 | False | 2025-08-10T13:55:30Z | 2025-10-25T13:20:10Z | transformers | 710 | 0 | null | image-text-to-text | {"parameters": {"F32": 5760, "BF16": 107710927360}, "total": 107710933120} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model-00001-of-00046.safetensors",
"model-00002-of-00046.safetensors",
"model-00003-of-00046.safetensors",
"model-00004-of-00046.safetensors",
"model-00005-of-00046.safetensors",
"model-00006-of-00046... | ed47433b37111465ec527affaaddceff371bca04 | [
"transformers",
"safetensors",
"glm4v_moe",
"image-text-to-text",
"conversational",
"zh",
"en",
"arxiv:2507.01006",
"base_model:zai-org/GLM-4.5-Air-Base",
"base_model:finetune:zai-org/GLM-4.5-Air-Base",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Glm4vMoeForConditionalGeneration"], "model_type": "glm4v_moe", "tokenizer_config": {"eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}, "chat_template_jinja": "[gMASK]<sop>\n{%- if tools -%}\n<|system|>\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["zai-org/GLM-4.5-Air-Base"], "datasets": null, "eval_results": null, "language": ["zh", "en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null} | # GLM-4.5V
<div align="center">
<img src=https://raw.githubusercontent.com/zai-org/GLM-V/refs/heads/main/resources/logo.svg width="40%"/>
</div>
This model is part of the GLM-V family of models, introduced in the paper [GLM-4.1V-Thinking and GLM-4.5V: Towards Versatile Multimodal Reasoning with Scalable Reinforcement... | null | [
"mit"
] | null | [
"zh",
"en"
] | 107,710,933,120 | null | null | [
"AutoModelForImageTextToText",
"Glm4vMoeForConditionalGeneration",
"glm4v_moe"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
67b38d4af31fc64e551b9adc | 5913c555399afcb0 | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | true | true | true | 249 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 147 | google/siglip2-base-patch32-256 | google | null | 3,051 | 191,053 | False | 2025-02-17T19:26:02Z | 2025-02-21T04:02:45Z | transformers | 13 | 0 | null | zero-shot-image-classification | {"parameters": {"F32": 376856066}, "total": 376856066} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"preprocessor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 94dffa8cb1179de3e03f091dbc3917e5d5a9ae84 | [
"transformers",
"safetensors",
"siglip",
"vision",
"zero-shot-image-classification",
"arxiv:2502.14786",
"arxiv:2303.15343",
"arxiv:2209.06794",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"model_type": "siglip", "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Convers... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "zero-shot-image-classification", "tags": ["vision"], "widget": [{"src": "https://huggi... | null | null | [
"apache-2.0"
] | null | null | 376,856,066 | null | null | [
"AutoModel",
"siglip"
] | [
null,
"zero-shot-image-classification"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"logits"
] |
621ffdc136468d709f1802fc | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | sentence-transformers/stsb-distilroberta-base-v2 | sentence-transformers | null | 527 | 175,263 | False | 2022-03-02T23:29:05Z | 2025-03-06T13:23:10Z | sentence-transformers | 2 | 0 | null | sentence-similarity | {"parameters": {"I64": 514, "F32": 82118400}, "total": 82118914} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"flax_model.msgpack",
"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",
... | c5319c5ec2eb7cb173d9756028b87c90c8f2c411 | [
"sentence-transformers",
"pytorch",
"tf",
"jax",
"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/stsb-distilroberta-base-v2
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... | null | [
"apache-2.0"
] | null | null | 82,118,914 | null | null | [
"roberta",
"AutoModel",
"RobertaModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
6628e4587ef8a073dda15122 | 39b1e434a495263c | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 349 | jondurbin/bagel-8b-v1.0 | jondurbin | {
"models": [
{
"_id": "661f97d48e7f3438386f755d",
"id": "meta-llama/Meta-Llama-3-8B"
}
],
"relation": "finetune"
} | 7,860 | 206,688 | False | 2024-04-24T10:52:08Z | 2024-05-12T20:48:33Z | transformers | 52 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"bagel.png",
"config.json",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"token... | b7f4d46d8a935623a47c9d6b3845443f20413a5f | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-3",
"bagel",
"conversational",
"dataset:ai2_arc",
"dataset:allenai/ultrafeedback_binarized_cleaned",
"dataset:argilla/distilabel-intel-orca-dpo-pairs",
"dataset:jondurbin/airoboros-3.2",
"dataset:codeparrot/apps",
"dataset:fac... | 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": "meta-llama/Meta-Llama-3-8B", "datasets": ["ai2_arc", "allenai/ultrafeedback_binarized_cleaned", "argilla/distilabel-intel-orca-dpo-pairs", "jondurbin/airoboros-3.2", "codeparrot/apps", "facebook/belebele", "bluemoon-fandom-1-1-rp-cleaned", "boolq", "camel-ai/biology", "camel-ai/chemistry", "camel-ai/mat... | # A bagel, with everything (except DPO)
## Overview
The name of this model is "llama-3-bagel-8b-v1.0" and it was built with llama-3 from Meta.
This is a fine-tune of llama-3-8b using the bagel dataset, but instead of 4 prompt formats it's standardized on a single format - llama-3 instruct.
See ... | null | [
"other",
"llama3",
"https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE"
] | [
"ai2_arc",
"allenai/ultrafeedback_binarized_cleaned",
"argilla/distilabel-intel-orca-dpo-pairs",
"jondurbin/airoboros-3.2",
"codeparrot/apps",
"facebook/belebele",
"bluemoon-fandom-1-1-rp-cleaned",
"boolq",
"camel-ai/biology",
"camel-ai/chemistry",
"camel-ai/math",
"camel-ai/physics",
"jondu... | null | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17b1bb | c554097f02b51501 | 7f079e4c59cc597c | 32,003 | Unigram | null | true | true | true | true | 3 | Sequence | Sequence | Metaspace | [
"Nmt",
"NFKC",
"Replace",
"Lowercase"
] | [
"Metaspace",
"Digits",
"Punctuation"
] | [
"Metaspace"
] | 767 | flax-community/spanish-t5-small | flax-community | null | 127 | 168,577 | False | 2022-03-02T23:29:05Z | 2023-03-17T01:03:00Z | transformers | 13 | 0 | null | null | {"parameters": {"F32": 60493824}, "total": 60493824} | [
".gitattributes",
"README.md",
"__pycache__/t5_tokenizer_model.cpython-38.pyc",
"config.json",
"events.out.tfevents.1626092365.t1v-n-563c3e20-w-0.115517.3.v2",
"events.out.tfevents.1626344166.t1v-n-563c3e20-w-0.335673.3.v2",
"events.out.tfevents.1626359070.t1v-n-563c3e20-w-0.350289.3.v2",
"events.out.... | 37a7d1ce23d20605a705b098e9ef705d8a3e9b2a | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"T5",
"Seq2Seq",
"EconderDecoder",
"Spanish",
"es",
"dataset:large_spanish_corpus",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5"} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["large_spanish_corpus"], "eval_results": null, "language": "es", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["T5", "Seq2Seq", "EconderDecoder", "Spanish"], "widgets": [{"text": "... | # Spanish T5 (small) trained on [large_spanish_corpus](https://huggingface.co/datasets/viewer/?dataset=large_spanish_corpus).
This is a Spanish **T5** (small arch) trained from scratch on the [large_spanish_corpus](https://huggingface.co/datasets/viewer/?dataset=large_spanish_corpus) aka BETO's corpus with [Flax](http... | null | [
"mit"
] | [
"large_spanish_corpus"
] | [
"es"
] | 60,493,824 | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
66333832ab69b961af56d7be | e796a3280e8bdc8e | acbc6a5df4443f8d | 128,288 | BPE | 280,147 | false | true | true | true | 288 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 768 | vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B | vicgalle | {
"models": [
{
"_id": "66303852b8d7220d89548ffc",
"id": "NousResearch/Hermes-2-Pro-Llama-3-8B"
}
],
"relation": "finetune"
} | 10,381 | 217,426 | False | 2024-05-02T06:52:34Z | 2024-07-31T16:38:50Z | transformers | 6 | 0 | [{"name": "Configurable-Hermes-2-Pro-Llama-3-8B", "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": 57.63, "n... | text-generation | {"parameters": {"F16": 8030523392}, "total": 8030523392} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"... | 82e7ca13eaa4e5110aee050f5e7076a1571fe604 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"safety",
"conversational",
"dataset:vicgalle/configurable-system-prompt-multitask",
"arxiv:2404.00495",
"base_model:NousResearch/Hermes-2-Pro-Llama-3-8B",
"base_model:finetune:NousResearch/Hermes-2-Pro-Llama-3-8B",
"license:apache-2.0",... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{bos_token}}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "NousResearch/Hermes-2-Pro-Llama-3-8B", "datasets": ["vicgalle/configurable-system-prompt-multitask"], "library_name": "transformers", "license": "apache-2.0", "tags": ["safety"], "model-index": [{"name": "Configurable-Hermes-2-Pro-Llama-3-8B", "results": [{"task": {"type": "text-generation", "name": "Te... | # Configurable-LLama-3-8B
A configurable NousResearch/Hermes-2-Pro-Llama-3-8B fine-tuned using the approach *configurable safety tuning* (CST) from https://arxiv.org/abs/2404.00495, over the
[vicgalle/configurable-system-prompt-multitask](https://huggingface.co/datasets/vicgalle/configurable-system-prompt-multitask) ... | null | [
"apache-2.0"
] | [
"vicgalle/configurable-system-prompt-multitask"
] | null | 8,030,523,392 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65aa615ab68db4f26ed17b8a | 18a54b681c3087de | 7ce118731980e5c6 | 29,794 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 769 | danielribeiro/google-play-sentiment-analysis | danielribeiro | {
"models": [
{
"_id": "621ffdc136468d709f17e62a",
"id": "neuralmind/bert-large-portuguese-cased"
}
],
"relation": "finetune"
} | 8 | 168,041 | False | 2024-01-19T11:47:38Z | 2024-01-26T00:35:51Z | transformers | 0 | 0 | [{"name": "google-play-sentiment-analysis", "results": []}] | text-classification | {"parameters": {"F32": 334399491}, "total": 334399491} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"runs/Jan19_11-40-06_a866c491d955/events.out.tfevents.1705664413.a866c491d955.261.0",
"runs/Jan25_11-02-12_9faf3daeb10e/events.out.tfevents.1706180598.9faf3daeb10e.600.0",
"runs/Jan26_00-12-41_e85bf87a225f/events.out.tfevents.1706228858.... | 0e8786915c667c58d3aaadf0c0362fb6031dafe1 | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:neuralmind/bert-large-portuguese-cased",
"base_model:finetune:neuralmind/bert-large-portuguese-cased",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:... | 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": "neuralmind/bert-large-portuguese-cased", "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": "google-play-sentiment-analysis", "pipeline_tag": null, "tags": ["generated_from_tra... | <!-- 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. -->
# google-play-sentiment-analysis
This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface... | null | [
"mit"
] | null | null | 334,399,491 | null | [
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
678e4022b7d37cc2f9b732f5 | 36935258f89e8e9e | 83d37c6e8ee56b77 | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 315 | unsloth/DeepSeek-R1-Distill-Qwen-1.5B-bnb-4bit | unsloth | {
"models": [
{
"_id": "678e11922b39b4ed1381531b",
"id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
}
],
"relation": "quantized"
} | 4,995 | 176,514 | False | 2025-01-20T12:22:58Z | 2025-02-14T23:54:41Z | transformers | 11 | 0 | null | text-generation | {"parameters": {"F32": 133280, "BF16": 466892288, "U8": 1351206570}, "total": 1818232138} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
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] | c6198f4cd0922d6d850bac1ae8719935d621a5c4 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"deepseek",
"qwen",
"unsloth",
"conversational",
"en",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"license:apache-2.0",
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"en... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_ge... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"base_model": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B", "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": ["deepseek", "qwen", "qwen2", "u... | ## ***See [our collection](https://huggingface.co/collections/unsloth/deepseek-r1-all-versions-678e1c48f5d2fce87892ace5) for versions of Deepseek R1 including GGUF and original formats.***
# Finetune LLMs 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) he... | null | [
"apache-2.0"
] | null | [
"en"
] | 1,818,232,138 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
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"text-generation"
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"text"
] | [
"text"
] | [
"text"
] |
685f87e689857bfda5eb03cc | bc23e733a7166c39 | 61daf977e586b75c | 101,304 | BPE | 182,926 | true | false | true | true | 1,029 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 487 | baidu/ERNIE-4.5-21B-A3B-Base-PT | baidu | null | 3,302 | 267,741 | False | 2025-06-28T06:12:54Z | 2025-11-26T08:00:12Z | transformers | 31 | 1 | null | text-generation | null | [
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<a href="https://ernie.baidu.com/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/🤖_Chat-ERNIE_Bot-blue" style="display: inline-block; vertical-align: middle;"/>
</a>
<a href="https://huggingface.co/baidu" target="_blank" s... | null | [
"apache-2.0"
] | null | [
"en",
"zh"
] | null | null | null | [
"Ernie4_5_MoeForCausalLM",
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"text"
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66c4fa54faf1c11450affe79 | f5e7f943c396c76b | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 52 | unsloth/Phi-3.5-mini-instruct | unsloth | {
"models": [
{
"_id": "66bfbb1a43a701a837a745ac",
"id": "microsoft/Phi-3.5-mini-instruct"
}
],
"relation": "finetune"
} | 4,086 | 189,147 | False | 2024-08-20T20:19:32Z | 2024-11-22T07:24:57Z | transformers | 46 | 0 | null | text-generation | {"parameters": {"BF16": 3821079552}, "total": 3821079552} | [
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] | a6499caf2e110c55af5e1348638b6454467412ae | [
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... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{% if message['role'] == 'system' and message['content'] %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + mess... | {
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} | {"base_model": "microsoft/Phi-3.5-mini-instruct", "datasets": null, "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": "https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE", "metrics": null, "model_name": nu... | # Finetune Phi-3.5, Llama 3.1, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Phi-3.5 (mini) here: https://colab.research.google.com/drive/1lN6hPQveB_mHSnTOYifygFcrO8C1bxq4?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/D... | null | [
"mit",
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] | null | [
"multilingual"
] | 3,821,079,552 | null | null | [
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"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
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] | [
"text"
] | [
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] |
632c55494a4991e71151c4ff | 2d0341bd3a73bae6 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 32 | Intel/t5-small-xsum-int8-dynamic-inc | Intel | null | 998 | 174,741 | False | 2022-09-22T12:30:01Z | 2024-03-21T12:59:37Z | transformers | 1 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
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] | 2f02c5e3d69392a9300ad89442d2978303bdd742 | [
"transformers",
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"t5",
"text2text-generation",
"int8",
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"neural-compressor",
"PostTrainingDynamic",
"dataset:mnli",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
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} | {"base_model": null, "datasets": ["mnli"], "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["int8", "Intel\u00ae Neural Compressor", "neural-compressor", "PostTra... | # INT8 T5 small finetuned on XSum
### Post-training dynamic quantization
This is an INT8 PyTorch model quantized with [huggingface/optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [Intel® Neural Compressor](https://github.com/intel/neural-compressor).
The original fp32 model comes ... | null | [
"apache-2.0"
] | [
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] | null | null | null | [
"accuracy"
] | [
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] | null | null | null |
621ffdc036468d709f17432a | a3d54d6c1d5c62b4 | f87d7bfce4fd9617 | 30,000 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Replace",
"Replace",
"NFKD",
"StripAccents",
"Lowercase",
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 12 | albert/albert-large-v1 | albert | null | 713 | 171,244 | False | 2022-03-02T23:29:04Z | 2024-02-19T10:58:26Z | transformers | 3 | 0 | null | fill-mask | null | [
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] | 94fd741fb5d6cb5bc578fc154837016c583bafef | [
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"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT Large v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | null | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
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666c0dd5b955b0e655d5d893 | 3f287b04362fff24 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 158 | OpenRLHF/Llama-3-8b-sft-mixture | OpenRLHF | null | 1,611 | 176,060 | False | 2024-06-14T09:31:01Z | 2024-06-14T11:21:59Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
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"... | 03334dc4a796d9d72850ead46956c33da22e6d7b | [
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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 %}{% for message in messages %}{{'<|start_header_id|>' + message['role'] + '<|end_header_id... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": []} | >Copy from https://huggingface.co/RLHFlow/LLaMA3-SFT
>
>We fixed the `generation_config.json`.
This is the SFT checkpoint used for the project [Online-RLHF](https://github.com/RLHFlow/Online-RLHF). Also, check the [technical report here](https://arxiv.org/pdf/2405.07863).
The model is trained from [meta-llama/Meta-L... | null | null | null | null | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
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680d15e5bad610f10bbe82a8 | b059c491175a21af | a301aa20b151814b | 128,264 | BPE | 280,147 | false | true | true | true | 264 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 770 | fdtn-ai/Foundation-Sec-8B | fdtn-ai | {
"models": [
{
"_id": "66944f1fe0c5c2e493a804f5",
"id": "meta-llama/Llama-3.1-8B"
}
],
"relation": "finetune"
} | 6,850 | 199,999 | False | 2025-04-26T17:20:37Z | 2025-08-26T01:32:36Z | transformers | 300 | 2 | null | text-generation | {"parameters": {"BF16": 8031309824}, "total": 8031309824} | [
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"en",
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"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|end_of_text|>", "pad_token": "<|end_of_text|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["meta-llama/Llama-3.1-8B"], "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": "text-generation", "tags": ["security"]} | # Foundation-Sec-8B - Model Card
## Model Information
Foundation-Sec-8B (Llama-3.1-FoundationAI-SecurityLLM-base-8B) is an open-weight, 8-billion parameter base language model specialized for cybersecurity applications. It extends Llama-3.1-8B model through continued pretraining on a curated corpus of cybersecurity-s... | null | [
"apache-2.0"
] | null | [
"en"
] | 8,031,309,824 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
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] | [
"text"
] | [
"text"
] |
635e021e4fabde0df74c67a7 | e500d06058ed22e0 | 8177c03aff392891 | 62,000 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 771 | NlpHUST/vi-word-segmentation | NlpHUST | null | 1,233 | 185,228 | False | 2022-10-30T04:48:30Z | 2022-10-30T09:45:24Z | transformers | 5 | 0 | [{"name": "vi-word-segmentation", "results": []}] | token-classification | null | [
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"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
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] | 8024ff7db9ccf201b386331ca8e59563daa51bc4 | [
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"pytorch",
"electra",
"token-classification",
"word segmentation",
"vi",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["ElectraForTokenClassification"], "model_type": "electra", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": ["vi"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": "vi-word-segmentation", "pipeline_tag": null, "tags": ["word segmentation"], "widget": [{"... | <!-- 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. -->
# vi-word-segmentation
This model is a fine-tuned version of [NlpHUST/electra-base-vn](https://huggingface.co/NlpHUST/electra-base-... | null | null | null | [
"vi"
] | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"ElectraForTokenClassification",
"AutoModelForTokenClassification",
"electra"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64afe8bac6cae3c050023a56 | 84892a81d307796d | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 133 | upstage/llama-30b-instruct-2048 | upstage | null | 849 | 171,144 | False | 2023-07-13T12:06:18Z | 2023-08-03T22:02:40Z | transformers | 102 | 0 | null | text-generation | null | [
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"pytorch_model-00001-of-00007.bin",
"pytorch_model-00002-of-00007.bin",
"pytorch_model-00003-of-00007.bin",
"pytorch_model-00004-of-00007.bin",
"pytorch_model-00005-of-00007.bin",
"pytorch_model-00006-of-00007.bin",
"pytorch... | 9f246be5c6c08bf397ff7b42aa5fe91d011d9ace | [
"transformers",
"pytorch",
"llama",
"text-generation",
"upstage",
"instruct",
"instruction",
"en",
"dataset:sciq",
"dataset:metaeval/ScienceQA_text_only",
"dataset:GAIR/lima",
"dataset:Open-Orca/OpenOrca",
"dataset:openbookqa",
"text-generation-inference",
"endpoints_compatible",
"depl... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["sciq", "metaeval/ScienceQA_text_only", "GAIR/lima", "Open-Orca/OpenOrca", "openbookqa"], "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",... | # LLaMa-30b-instruct-2048 model card
## Model Details
* **Developed by**: [Upstage](https://en.upstage.ai)
* **Backbone Model**: [LLaMA](https://github.com/facebookresearch/llama/tree/llama_v1)
* **Variations**: It has different model parameter sizes and sequence lengths: [30B/1024](https://huggingface.co/upstage/lla... | null | null | [
"sciq",
"metaeval/ScienceQA_text_only",
"GAIR/lima",
"Open-Orca/OpenOrca",
"openbookqa"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
642fc692550e13b83277fa85 | 98e5292f74970347 | 3223918073c8709d | 50,260 | BPE | 50,000 | false | true | true | true | 4 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 772 | vicgalle/gpt2-alpaca | vicgalle | null | 1,925 | 182,843 | False | 2023-04-07T07:30:26Z | 2023-11-30T10:41:10Z | transformers | 9 | 0 | null | text-generation | {"parameters": {"F32": 124442112, "U8": 12582912}, "total": 137025024} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | dd90aae6879accb7ba273e24b7531b18654c7574 | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"instruct-tuning",
"alpaca",
"en",
"dataset:tatsu-lab/alpaca",
"doi:10.57967/hf/1409",
"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": ["tatsu-lab/alpaca"], "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": ["instruct-tuning", "gpt2", "alpaca"]} | # GPT2 finetuned with Alpaca
### 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:
Give thr... | null | [
"mit"
] | [
"tatsu-lab/alpaca"
] | [
"en"
] | 137,025,024 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6592ac0fc27d210c3ed488e7 | 89a5128d694e9242 | 081b543d8f95004e | 32,002 | BPE | 58,980 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 419 | TheBloke/dolphin-2.7-mixtral-8x7b-AWQ | TheBloke | {
"models": [
{
"_id": "65913a83c04427eb38a32e4a",
"id": "dphn/dolphin-2.7-mixtral-8x7b"
}
],
"relation": "quantized"
} | 3,676 | 188,388 | False | 2024-01-01T12:11:59Z | 2024-01-01T19:07:25Z | transformers | 23 | 0 | null | text-generation | {"parameters": {"I32": 46439333888, "F16": 263475200}, "total": 46702809088} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"eval_results.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"quant_config.json",
"special_tokens_map... | 6748ac0806dff88166a8c2b3d976d94d03c70687 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"conversational",
"en",
"dataset:ehartford/dolphin",
"dataset:jondurbin/airoboros-2.2.1",
"dataset:ehartford/dolphin-coder",
"dataset:teknium/openhermes",
"dataset:ise-uiuc/Magicoder-OSS-Instruct-75K",
"dataset:ise-uiuc/Magicoder-Evo... | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_sta... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "cognitivecomputations/dolphin-2.7-mixtral-8x7b", "datasets": ["ehartford/dolphin", "jondurbin/airoboros-2.2.1", "ehartford/dolphin-coder", "teknium/openhermes", "ise-uiuc/Magicoder-OSS-Instruct-75K", "ise-uiuc/Magicoder-Evol-Instruct-110K", "LDJnr/Capybara"], "eval_results": null, "language": ["en"], "l... | <!-- markdownlint-disable MD041 -->
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content:... | null | [
"apache-2.0"
] | [
"ehartford/dolphin",
"jondurbin/airoboros-2.2.1",
"ehartford/dolphin-coder",
"teknium/openhermes",
"ise-uiuc/Magicoder-OSS-Instruct-75K",
"ise-uiuc/Magicoder-Evol-Instruct-110K",
"LDJnr/Capybara"
] | [
"en"
] | 46,702,809,088 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65b7690ed73977130c8830a7 | f7439c5fb4111c3a | f91ee9c261d96b92 | 48,384 | BPE | 81,735 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 773 | SeaLLMs/SeaLLM-7B-v2 | SeaLLMs | null | 8,697 | 209,463 | False | 2024-01-29T08:59:58Z | 2024-07-24T06:36:05Z | transformers | 68 | 0 | null | text-generation | {"parameters": {"BF16": 7375949824}, "total": 7375949824} | [
".gitattributes",
"README.md",
"config.json",
"evaluation/.DS_Store",
"evaluation/mt_bench/gpt-4_single_seallm_7b_v2.jsonl",
"evaluation/mt_bench/seallm_7b_v2.jsonl",
"evaluation/sea_bench/seallm_7b_v2.jsonl",
"fig_sea_bench_side_by_side.png",
"fig_sea_math_side_by_side.png",
"model.safetensors",
... | 04d5d6102eb0865f4a0ca55fe8d12478605748f8 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"multilingual",
"sea",
"conversational",
"en",
"zh",
"vi",
"id",
"th",
"ms",
"km",
"lo",
"my",
"tl",
"arxiv:2312.00738",
"arxiv:2205.11916",
"arxiv:2306.05179",
"arxiv:2306.05685",
"license:other",
"text-generat... | 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, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "zh", "vi", "id", "th", "ms", "km", "lo", "my", "tl"], "library_name": null, "license": "other", "license_name": "seallms", "license_link": "https://huggingface.co/SeaLLMs/SeaLLM-13B-Chat/blob/main/LICENSE", "metrics": null, "model_name": n... | <p align="center">
<img src="seal_logo.png" width="200" />
</p>
# *SeaLLM-7B-v2* - Large Language Models for Southeast Asia
# <strong style="color: red">BIG NEWS: <a href="https://huggingface.co/SeaLLMs/SeaLLM3-7B-Chat">SeaLLM3</a> is released with state-of-the-art performance of diverse tasks while specifically en... | null | [
"other",
"seallms",
"https://huggingface.co/SeaLLMs/SeaLLM-13B-Chat/blob/main/LICENSE"
] | null | [
"en",
"zh",
"vi",
"id",
"th",
"ms",
"km",
"lo",
"my",
"tl"
] | 7,375,949,824 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65acf73dc14c3cf579a3d9d4 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | vicgalle/CarbonBeagle-11B | vicgalle | {
"models": [
{
"_id": "65904ccba78a277803bfb761",
"id": "jeonsworld/CarbonVillain-en-10.7B-v4"
},
{
"_id": "65ab9a168abada9cc15a5455",
"id": "vicgalle/NeuralBeagle-11B"
}
],
"relation": "merge"
} | 7,858 | 204,307 | False | 2024-01-21T10:51:41Z | 2025-06-24T15:28:23Z | transformers | 9 | 0 | [{"name": "CarbonBeagle-11B", "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": 71.84, "name": "norm... | text-generation | {"parameters": {"F16": 10731524096}, "total": 10731524096} | [
".gitattributes",
"README.md",
"config.json",
"mergekit_config.yml",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.jso... | 9a2a5868d787af514e010ce52751ede5da5af115 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2203.05482",
"base_model:jeonsworld/CarbonVillain-en-10.7B-v4",
"base_model:merge:jeonsworld/CarbonVillain-en-10.7B-v4",
"base_model:vicgalle/NeuralBeagle-11B",
"base_model:merge:vicgalle... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "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' %}{{'### Us... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["vicgalle/NeuralBeagle-11B", "jeonsworld/CarbonVillain-en-10.7B-v4"], "license": "cc-by-nc-sa-4.0", "tags": ["mergekit", "merge"], "model-index": [{"name": "CarbonBeagle-11B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Sh... | # CarbonBeagle-11B
An experiment in merging models of different architectures and sizes. Here are the steps:
1. Upscale mlabonne/NeuralBeagle14-7B to vicgalle/franken-Beagle-11B.
2. DPO-tune vicgalle/franken-Beagle-11B to vicgalle/NeuralBeagle-11B.
3. Merge vicgalle/NeuralBeagle-11B and jeonsworld/CarbonVillain-en-10... | null | [
"cc-by-nc-sa-4.0"
] | null | null | 10,731,524,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
640bb155548fcf9a11909491 | 323b73c86b26d5cc | 1076b26951579e31 | 50,262 | BPE | 50,000 | false | true | true | true | 6 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 774 | Amisha182001/autodescgpt2 | Amisha182001 | null | 12 | 166,210 | False | 2023-03-10T22:38:13Z | 2023-03-10T22:40:40Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | d72d597d1b29226c3ff8e850decda08b0d38b10c | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"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"
} | null | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67ac1f09425ab9c458000cbb | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | NousResearch/DeepHermes-3-Llama-3-8B-Preview | NousResearch | {
"models": [
{
"_id": "66944f1fe0c5c2e493a804f5",
"id": "meta-llama/Llama-3.1-8B"
}
],
"relation": "finetune"
} | 236 | 167,576 | False | 2025-02-12T04:09:45Z | 2025-04-10T17:22:44Z | transformers | 351 | 0 | [{"name": "DeepHermes-3-Llama-3.1-8B", "results": []}] | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"... | 53d902c7dcfa4c749a3b455149064f82af2e2549 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"Llama-3",
"instruct",
"finetune",
"chatml",
"gpt4",
"synthetic data",
"distillation",
"function calling",
"json mode",
"axolotl",
"roleplaying",
"chat",
"reasoning",
"r1",
"vllm",
"conversational",
"en",
"base_mode... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": [{"name": "default", "template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Meta-Llama-3.1-8B", "datasets": null, "eval_results": [], "language": ["en"], "library_name": "transformers", "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": "DeepHermes-3-Llama-3.1-8B", "pipeline_tag": null, "tags": ["Llama-3", "instruct", "fin... | # DeepHermes 3 - Llama-3.1 8B
## Model Description
DeepHermes 3 Preview is the latest version of our flagship Hermes series of LLMs by Nous Research, and one of the first models in the world to un... | null | [
"llama3"
] | null | [
"en"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67a516cab2035609509fc2e3 | aae46bd9736d5fc4 | 7d90101667cac12d | 30,000 | WordPiece | null | true | true | true | true | 5 | Sequence | Split | WordPiece | [
"NFD",
"StripAccents"
] | [
"Split"
] | [
"WordPiece"
] | 775 | syssec-utd/py311-pylingual-v1-segmenter | syssec-utd | {
"models": [
{
"_id": "67a46abe744174137dfae6ed",
"id": "syssec-utd/py311-pylingual-v1-mlm"
}
],
"relation": "finetune"
} | 22,125 | 246,921 | False | 2025-02-06T20:08:42Z | 2025-02-07T01:29:03Z | transformers | 0 | 0 | [{"name": "py311-pylingual-v1-segmenter", "results": []}] | token-classification | {"parameters": {"F32": 108493827}, "total": 108493827} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"runs/Feb06_14-07-52_tacosec0/events.out.tfevents.1738872522.tacosec0.1855552.0",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | db194efaa37d0b6b46b5bf296e43b061f131c907 | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"token-classification",
"generated_from_trainer",
"base_model:syssec-utd/py311-pylingual-v1-mlm",
"base_model:finetune:syssec-utd/py311-pylingual-v1-mlm",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForTokenClassification"], "model_type": "roberta", "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": "syssec-utd/py311-pylingual-v1-mlm", "datasets": null, "eval_results": [], "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": "py311-pylingual-v1-segmenter", "pipeline_tag": nul... | null | null | null | null | null | 108,493,827 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"roberta",
"AutoModelForTokenClassification",
"RobertaForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
66615424221a94f56bb9032e | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/Qwen2-1.5B-Instruct-GPTQ-Int4 | Qwen | {
"models": [
{
"_id": "665d87fc0f43f1c4ad1ce2a1",
"id": "Qwen/Qwen2-1.5B-Instruct"
}
],
"relation": "quantized"
} | 20,875 | 240,884 | False | 2024-06-06T06:16:04Z | 2024-08-21T10:36:01Z | transformers | 5 | 0 | null | text-generation | {"parameters": {"F32": 466834944, "I32": 1310195712, "F16": 645120}, "total": 1777675776} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | b2e2d7e4336e61901d421296d0a1f418b1a93ae7 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"base_model:Qwen/Qwen2-1.5B-Instruct",
"base_model:quantized:Qwen/Qwen2-1.5B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"gptq",
"deploy:azure",
... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|i... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-1.5B-Instruct", "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": "text-generation", "tags": ["chat"]} | # Qwen2-1.5B-Instruct-GPTQ-Int4
## Introduction
Qwen2 is the new series of Qwen large language models. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the instruction-tuned ... | null | [
"apache-2.0"
] | null | [
"en"
] | 1,777,675,776 | null | null | [
"AutoModelForCausalLM",
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"qwen2"
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"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Precompiled"
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"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | google/switch-base-32 | google | null | 158 | 166,481 | False | 2022-11-04T07:58:49Z | 2023-11-28T09:43:25Z | transformers | 10 | 0 | null | null | {"parameters": {"F32": 1978514688}, "total": 1978514688} | [
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"en",
"dataset:c4",
"arxiv:2101.03961",
"arxiv:1910.09700",
"license:apache-2.0",
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] | null | {"architectures": ["SwitchTransformersForConditionalGeneration"], "model_type": "switch_transformers", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
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} | {"base_model": null, "datasets": ["c4"], "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": ["text2text-generation"], "widget": [{"text": "The <extra_id_0> walks in <extra... | # Model Card for Switch Transformers Base - 32 experts
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Usage](#usage)
3. [Uses](#uses)
4. [Bias, Risks, and Limitations](#bias-r... | null | [
"apache-2.0"
] | [
"c4"
] | [
"en"
] | 1,978,514,688 | null | null | [
"AutoModelForSeq2SeqLM",
"SwitchTransformersForConditionalGeneration",
"switch_transformers"
] | [
"text2text-generation"
] | null | null | null |
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"Split",
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"ByteLevel"
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"auto_model": "AutoModelForCausalLM",
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The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue us... | null | [
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"ByteLevel"
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} | 6,264 | 191,965 | False | 2024-10-02T21:07:46Z | 2024-12-19T19:45:46Z | transformers | 49 | 1 | [{"name": "granite-3.0-2b-instruct", "results": [{"task": {"type": "text-generation"}, "dataset": {"type": "instruction-following", "name": "IFEval"}, "metrics": [{"name": "pass@1", "type": "pass@1", "value": 46.07, "veriefied": false, "verified": false}]}, {"task": {"type": "text-generation"}, "dataset": {"type": "ins... | text-generation | {"parameters": {"BF16": 2634201088}, "total": 2634201088} | [
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<!--  -->
# Granite-3.0-2B-Instruct
<!-- **Note: We are continuously improving our models and recommend users to checkout our latest [Gra... | null | [
"apache-2.0"
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687ed8c5c72e5453c302bc36 | 46323c0f61df476d | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
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"Replace",
"ByteFallback",
"Fuse"
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This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 5,639,504 | null | null | [
"AutoModelForImageTextToText",
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- 2024.01.08: Initial Test version Release of Solar-Ko
# **Open-Solar-Ko** ⭐🇰🇷
Solar-Ko represents an advanced iteration of the upstage/SOLAR-10.7B-v1.0 model, featuring an expanded vocabulary and the inclusion of a Korean corpus for enhanced pretraining.
Open-Solar-Ko exclusively utilizes publicl... | null | [
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} | 137 | 166,473 | False | 2023-04-18T07:46:03Z | 2023-09-15T01:28:23Z | transformers | 63 | 0 | [{"name": "KoAlpaca-Polyglot-12.8B", "results": []}] | text-generation | {"parameters": {"F16": 12892815360, "F32": 1280, "BOOL": 167772160}, "total": 13060588800} | [
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- Add Safetensor sharded model weight (max shard = 1GB)
# KoAlpaca-Polyglot-12.8B (v1.1b)
This model is a fine-tuned version of [EleutherAI/polyglot-ko-12.8b](https://huggingface.co/EleutherAI/polyglot-ko-12.8b) on a KoAlpaca Dataset v1.1b
Detail Codes are available at [KoAlpaca Github Reposito... | null | [
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"merges.txt",
"model-00001-of-00038.safetensors",
"model-00002-of-00038.safetensors",
"model-00003-of-00038.safetensors",
"model-00004-of-00038.safetensors",
"model-00005-of-00038.safetensors",
"model-00006-of-0... | 93bac0d1ae83d50c43b1793e2d74a00dc43a4c36 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"pretrained",
"conversational",
"en",
"arxiv:2309.16609",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "other", "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-72B/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["pret... | # Qwen1.5-72B
## Introduction
Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. In comparison with the previous released Qwen, the improvements include:
* 8 model sizes, including 0.5B, 1.8B, 4B, 7B, 14B, 32B and 72B dense models, and an MoE ... | null | [
"other",
"tongyi-qianwen",
"https://huggingface.co/Qwen/Qwen1.5-72B/blob/main/LICENSE"
] | null | [
"en"
] | 72,287,920,128 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66a00630867d02432987cacf | 21feada71fab2765 | 12ebeebff692ebb1 | 131,072 | BPE | 269,443 | false | true | true | true | 1,000 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 245 | shuyuej/Mistral-Nemo-Instruct-2407-GPTQ | shuyuej | null | 238 | 166,410 | False | 2024-07-23T19:36:16Z | 2024-07-25T02:09:51Z | transformers | 7 | 0 | null | text-generation | {"parameters": {"I32": 10905190400, "F16": 1342592000}, "total": 12247782400} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | f32426adc2b46de3b619b88e3e6d7e0c78a1000b | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"gptq",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content'] %}\n {%- set loop_messages = message... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # The Quantized Mistral Nemo Instruct 2407 Model
Original Base Model: `mistralai/Mistral-Nemo-Instruct-2407`.<br>
Link: [https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)
## Quantization Configurations
```
"quantization_config": {
"batch_size... | null | [
"apache-2.0"
] | null | null | 12,247,782,400 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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