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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk)
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# Parler-TTS Mini Multilingual v1.1
<a target="_blank" href="https://huggingface.co/spaces/PHBJT/multi_parler_tts">
<img src="https:... | null | [
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... | null | {"architectures": ["DebertaV2ForSequenceClassification"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
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This is a model based on [DeBERTaV3-base](https://huggingface.co/microsoft/deberta-v3-base) that was trained on natural language inference datasets as well as on multiple text classification datasets.
It demonstrates better quality on the diverse set of text classification datasets in a zero-s... | null | [
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] | null | {"architectures": ["SolarForCausalLM"], "auto_map": {"AutoConfig": "configuration_solar.SolarConfig", "AutoModelForCausalLM": "modeling_solar.SolarForCausalLM"}, "model_type": "solar", "tokenizer_config": {"bos_token": "<|startoftext|>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generati... | {
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<a href="https://go.upstage.ai/3Xk9J6X">
<img src="https://cdn-uploads.huggingface.co/production/uploads/5fd90c758fe27b1a6b077abb/jwMkqV88Hj8sJu7NjTedm.png" width="100%"/>
</a>
<p>
# **Solar Pro Preview: The most intelligent LLM on a single GPU**
# **Summary**
We introduce **Solar Pro Previe... | null | [
"mit",
"https://huggingface.co/upstage/solar-pro-preview-instruct/blob/main/LICENSE"
] | null | [
"en"
] | null | null | null | [
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"ByteLevel"
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"dataset:japanese-asr/whisper_transcriptions.reazo... | null | {"architectures": ["WhisperForConditionalGeneration"], "model_type": "whisper", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
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[**faster-whisper weight**](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-faster), [**whisper.cpp weight**](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml), [**pipeline with stable-ts/punctuation**](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.1)
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] | 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",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["snli"], "eval_results": [], "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": "roberta-base-snli", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-base-snli
This model was trained from scratch on the snli dataset.
It achieves the following results on the evaluation se... | null | null | [
"snli"
] | null | null | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65cbe5903a3b98c7761f131b | aed290a0124eb522 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 10 | annakotarba/sentence-similarity | annakotarba | null | 4 | 180,359 | False | 2024-02-13T21:56:32Z | 2024-02-13T21:56:54Z | sentence-transformers | 0 | 0 | null | sentence-similarity | {"parameters": {"F32": 117653760}, "total": 117653760} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"unigram.json"
] | 15b6a64cb5f4673fb5fc61fc1fbb75db7e7df23b | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"dataset:private",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["private"], "eval_results": null, "language": null, "library_name": "sentence-transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", ... | # annakotarba/sentence-similarity
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model ... | null | null | [
"private"
] | null | 117,653,760 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
66eb4447bd1051b7adab2234 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | unsloth/Qwen2.5-7B | unsloth | {
"models": [
{
"_id": "66e6d06401e2adb00b0be996",
"id": "Qwen/Qwen2.5-7B"
}
],
"relation": "finetune"
} | 137,093 | 387,881 | False | 2024-09-18T21:21:11Z | 2025-04-28T04:14:00Z | transformers | 8 | 0 | null | 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",
"special_to... | 86e6e1eccea424c7fb77d59f7d2a9125c0673bfd | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-7B",
"base_model:finetune:Qwen/Qwen2.5-7B",
"license:apache-2.0",
... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "eos_token": "<|endoftext|>", "pad_token": "<|vision_pad|>", "unk_token": null}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-7B", "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": null, "pi... | # 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"
] | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6511a5c5254ae1f9616eff92 | 8e42935d2dbeb45e | daab2a732bab72e2 | 128,001 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Strip",
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 204 | safepaca/absolute-harmfulness-predictor-redteam | safepaca | null | 24 | 164,333 | False | 2023-09-25T15:22:45Z | 2023-09-25T15:27:38Z | transformers | 1 | 0 | [{"name": "safetune", "results": []}] | text-classification | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"all_results.json",
"config.json",
"eval_results.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spm.model",
"tokenizer.json",
"tokenizer_config.json",
"train_results.json",
"trainer_state.json",
"training_args.bin"
] | 148a4d6297089a6dc4f024ebcbac1545552a928b | [
"transformers",
"pytorch",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DebertaV2ForSequenceClassification"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "safetune", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# safetune
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on... | null | [
"mit"
] | null | null | null | null | null | [
"AutoModelForSequenceClassification",
"deberta-v2",
"DebertaV2ForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
62d7ae339ccca9c822d09014 | dd8ef53ef5a0f56a | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 90 | jonaskoenig/topic_classification_04 | jonaskoenig | {
"models": [
{
"_id": "621ffdc136468d709f17df38",
"id": "microsoft/xtremedistil-l6-h256-uncased"
}
],
"relation": "finetune"
} | 30 | 164,215 | False | 2022-07-20T07:26:43Z | 2023-09-13T06:40:36Z | transformers | 27 | 0 | [{"name": "topic_classification_04", "results": []}] | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | e4fb1c91eb7f8d7ea3e78760b5f56631efcea50b | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"base_model:microsoft/xtremedistil-l6-h256-uncased",
"base_model:finetune:microsoft/xtremedistil-l6-h256-uncased",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": "microsoft/xtremedistil-l6-h256-uncased", "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "topic_classification_04", "pipeline_tag": null, "tags": ["generated_from_keras_callback"]} | <!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# topic_classification_04
This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft... | null | [
"mit"
] | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
63e5149b05565e7a3c783690 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | pierreguillou/lilt-xlm-roberta-base-finetuned-with-DocLayNet-base-at-linelevel-ml384 | pierreguillou | null | 2,447 | 167,986 | False | 2023-02-09T15:43:23Z | 2023-05-19T06:46:30Z | transformers | 12 | 0 | [{"name": "lilt-xlm-roberta-base-finetuned-with-DocLayNet-base-at-linelevel-ml384", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "metrics": [{"name": "f1", "type": "f1", "value": 0.8584, "verified": false}, {"name": "accuracy", "type": "accuracy", "value": 0.8584, "verified": f... | token-classification | null | [
".gitattributes",
"README.md",
"checkpoint-12000/config.json",
"checkpoint-12000/optimizer.pt",
"checkpoint-12000/pytorch_model.bin",
"checkpoint-12000/rng_state.pth",
"checkpoint-12000/scaler.pt",
"checkpoint-12000/scheduler.pt",
"checkpoint-12000/special_tokens_map.json",
"checkpoint-12000/token... | dc97047796aba7a19eef1fc7282891fa57fef577 | [
"transformers",
"pytorch",
"tensorboard",
"lilt",
"token-classification",
"object-detection",
"vision",
"generated_from_trainer",
"DocLayNet",
"COCO",
"PDF",
"IBM",
"Financial-Reports",
"Finance",
"Manuals",
"Scientific-Articles",
"Science",
"Laws",
"Law",
"Regulations",
"Pat... | null | {"architectures": ["LiltForTokenClassification"], "model_type": "lilt", "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_tok... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["pierreguillou/DocLayNet-base"], "eval_results": null, "language": ["multilingual", "en", "de", "fr", "ja"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": nul... | <!-- 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. -->
# Document Understanding model (finetuned LiLT base at line level on DocLayNet base)
This model is a fine-tuned version of [nielsr/... | null | [
"mit"
] | [
"pierreguillou/DocLayNet-base"
] | [
"multilingual",
"en",
"de",
"fr",
"ja"
] | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"lilt",
"LiltForTokenClassification"
] | [
"object-detection",
"token-classification",
"image-segmentation"
] | [
"text",
"multimodal"
] | [
"text",
"image"
] | [
"logits",
"image"
] |
6644924f34ec0631acb21e76 | f6bd53b02735a215 | 3f3879d485dc5e16 | 63,992 | BPE | 110,029 | true | false | false | true | 231 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 512 | 01-ai/Yi-1.5-9B-32K | 01-ai | null | 8,429 | 205,602 | False | 2024-05-15T10:45:35Z | 2024-06-26T10:43:03Z | transformers | 18 | 0 | null | text-generation | {"parameters": {"BF16": 8829407232}, "total": 8829407232} | [
".gitattributes",
"NOTICE",
"README.md",
"config.json",
"generation_config.json",
"md5",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"nohup.out",
"tokenizer.jso... | c0239dbc923b8a2b5ca849763bdd592d39c60850 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:2403.04652",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<|startoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<unk>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | <div align="center">
<picture>
<img src="https://raw.githubusercontent.com/01-ai/Yi/main/assets/img/Yi_logo_icon_light.svg" width="150px">
</picture>
</div>
<p align="center">
<a href="https://github.com/01-ai">🐙 GitHub</a> •
<a href="https://discord.gg/hYUwWddeAu">👾 Discord</a> •
<a href="https://twitter... | null | [
"apache-2.0"
] | null | null | 8,829,407,232 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63b2b7b90dddc8f717ef9cc3 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | microsoft/git-large-textcaps | microsoft | null | 600 | 167,916 | False | 2023-01-02T10:53:45Z | 2023-02-08T10:49:30Z | transformers | 30 | 0 | null | image-to-text | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"preprocessor_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 3fd449a0ee1397c50ce05b6f0fde381317d51e35 | [
"transformers",
"pytorch",
"git",
"image-text-to-text",
"vision",
"image-captioning",
"image-to-text",
"en",
"arxiv:2205.14100",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GitForCausalLM"], "model_type": "git", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "microsoft/git-large-textcaps", "pipeline_tag": "image-to-text", "tags": ["vision", "image-captioning"]} | # GIT (GenerativeImage2Text), large-sized, fine-tuned on TextCaps
GIT (short for GenerativeImage2Text) model, large-sized version, fine-tuned on TextCaps. It was introduced in the paper [GIT: A Generative Image-to-text Transformer for Vision and Language](https://arxiv.org/abs/2205.14100) by Wang et al. and first rele... | null | [
"mit"
] | null | [
"en"
] | null | null | null | [
"AutoModelForImageTextToText",
"GitForCausalLM",
"git"
] | [
"image-text-to-text",
"image-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
68f4d9f1645feb80d4568236 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | Qwen/Qwen3-VL-32B-Instruct | Qwen | null | 1,074,627 | 4,440,023 | False | 2025-10-19T12:30:41Z | 2025-10-21T18:26:34Z | transformers | 192 | 2 | null | image-text-to-text | {"parameters": {"BF16": 33357390064}, "total": 33357390064} | [
".gitattributes",
"README.md",
"chat_template.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00014.safetensors",
"model-00002-of-00014.safetensors",
"model-00003-of-00014.safetensors",
"model-00004-of-00014.safetensors",
"model-00005-of-00014.safetensors",
"model... | 0cfaf48183f594c314753d30a4c4974bc75f3ccb | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"conversational",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Qwen3VLForConditionalGeneration"], "model_type": "qwen3_vl", "processor_config": {"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {%- if messages[0].content is string %}\n {{- messages[0].content }}\n {%- el... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null} | null | null | [
"apache-2.0"
] | null | null | 33,357,390,064 | null | null | [
"AutoModelForImageTextToText",
"qwen3_vl",
"Qwen3VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
64e4e17ac7c084f92ac4adbd | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | anushehchaudry/llama-2-tiny-random | anushehchaudry | null | 17 | 163,080 | False | 2023-08-22T16:25:30Z | 2023-08-24T16:46:28Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F32": 513048}, "total": 513048} | [
".gitattributes",
"README.md",
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"model.safetensors",
"pytorch_model.bin",
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"tokenizer.model",
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] | c2f8a9287a665943bfb34466da859ed12ad2c40b | [
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"llama",
"text-generation",
"license:openrail",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": false, "rstrip... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "openrail", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | null | [
"openrail"
] | null | null | 513,048 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
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"text"
] | [
"text"
] | [
"text"
] |
65afdb5b49a955de36dd3b2a | 6717c178a9e02ec5 | 477ef93aefa1d4b1 | 48,000 | BPE | 58,980 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 780 | kimwooglae/WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34 | kimwooglae | null | 5 | 24 | False | 2024-01-23T15:29:31Z | 2024-01-23T15:58:44Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00005.bin",
"pytorch_model-00002-of-00005.bin",
"pytorch_model-00003-of-00005.bin",
"pytorch_model-00004-of-00005.bin",
"pytorch_model-00005-of-00005.bin",
"pytorch_model.bin.index.json",
"tokenizer.j... | 1bdfa772d590b9bebe1bb28e5efdbcce4bbc1c33 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"en",
"license:cc-by-nc-4.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "<|im_end|>", "pad_token": "</s>", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | # WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34
## Model Details
**Developed by**
[Inswave Systems](https://www.inswave.com) UI Platform Team
**Base Model**
[LDCC/LDCC-SOLAR-10.7B](https://huggingface.co/LDCC/LDCC-SOLAR-10.7B)
# Implementation Code
```python
from transformers import AutoModelForCausalLM, AutoTo... | null | [
"cc-by-nc-4.0"
] | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65e2a24775b43b925e680c3c | b49a267aede0010e | 46437d7a3d1ef041 | 32,005 | BPE | 58,980 | true | false | true | true | 8 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 781 | ibm-research/merlinite-7b | ibm-research | {
"models": [
{
"_id": "650aedb6238a644cb93a52c3",
"id": "mistralai/Mistral-7B-v0.1"
}
],
"relation": "finetune"
} | 219 | 162,728 | False | 2024-03-02T03:51:35Z | 2024-03-05T14:01:15Z | transformers | 105 | 0 | null | text-generation | {"parameters": {"BF16": 7241797632}, "total": 7241797632} | [
".gitattributes",
"Model Card for Merlinite 7b 28cc0b72cf574a4a828140d3539ede4a/Screenshot_2024-02-22_at_11.26.13_AM.png",
"Model Card for Merlinite 7b 28cc0b72cf574a4a828140d3539ede4a/Untitled 1.png",
"Model Card for Merlinite 7b 28cc0b72cf574a4a828140d3539ede4a/Untitled 2.png",
"Model Card for Merlinite 7... | 233d12759d5bb9344231dafdb51310ec19d79c0e | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merlinite",
"ibm",
"lab",
"labrador",
"labradorite",
"en",
"arxiv:2403.01081",
"base_model:mistralai/Mistral-7B-v0.1",
"base_model:finetune:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"text-generation-inference",
"endp... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "<|endoftext|>", "pad_token": "<|pad|>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "mistralai/Mistral-7B-v0.1", "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": ["merlinite", "mistral", "ibm", "lab", "labra... | # Model Card for Merlinite 7b 🔥 [Paper](https://arxiv.org/abs/2403.01081)
### Overview
### Performance
| Model | Alignment | Base | Teacher | MTBench (Avg) *... | null | [
"apache-2.0"
] | null | [
"en"
] | 7,241,797,632 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17b189 | eb1a01e072dcfe2e | b275321a1ff7afdc | 50,000 | BPE | 49,712 | false | true | true | true | 32 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 782 | flax-community/gpt2-medium-persian | flax-community | null | 96 | 162,644 | False | 2022-03-02T23:29:05Z | 2021-07-16T13:01:08Z | transformers | 10 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"events.out.tfevents.1625933109.t1v-n-a95a71e5-w-0.273188.3.v2",
"events.out.tfevents.1626033670.t1v-n-a95a71e5-w-0.441100.3.v2",
"flax_model.msgpack",
"merges.txt",
"notes/.keep",
"notes/Data_Preprocessing.ipynb",
"notes/Demo_datasets.ipynb",
"notes... | 5810babdec1f4c68888f2d80a7c2ab6e8aeb6fe0 | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"fa",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2"} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text-generation"], "widget": [{"text": "\u062f\u0631 \u06cc\u06a9 \u0627\u062a\u0641\u062... | # GPT2 Medium 4 Persian
> This is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/pretrain-gpt2-from-scratch-in-persian/7560), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
## Team Members
- [Mehrdad Farahani](huggingface.co/m3hrdadfi)
- [Saied Alimoradi... | null | null | null | [
"fa"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64c38b547918ee895ba3d422 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | KoboldAI/LLAMA2-13B-Holodeck-1 | KoboldAI | null | 13 | 162,108 | False | 2023-07-28T09:33:08Z | 2023-07-28T21:08:16Z | transformers | 23 | 0 | null | text-generation | {"parameters": {"F16": 13015864320}, "total": 13015864320} | [
".gitattributes",
"LICENSE.md",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00014.safetensors",
"model-00002-of-00014.safetensors",
"model-00003-of-00014.safetensors",
"model-00004-of-00014.safetensors",
"model-00005-of-00014.safetensors",
"model-00006-of-00014.safetens... | 18c3ffdba7a55f834b08aa4907a82337c9088fb4 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"en",
"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": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": false, "rstrip... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "commercial": "no", "inference": true} | # LLAMA2 13B - Holodeck
## Model Description
LLAMA2 13B-Holodeck is a finetune created using Meta's llama 2 model.
## Training data
The training data contains around 3000 ebooks in various genres.
Most parts of the dataset have been prepended using the following text: `[Genre: <genre1>, <genre2>]`
### How to use
You ca... | null | [
"other"
] | null | [
"en"
] | 13,015,864,320 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6826f46819465348a9752d61 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/WorldPM-72B-UltraFeedback | Qwen | {
"models": [
{
"_id": "6826f3ce82651bace36d9ba6",
"id": "Qwen/WorldPM-72B"
}
],
"relation": "finetune"
} | 618 | 165,835 | False | 2025-05-16T08:16:40Z | 2025-05-17T06:40:25Z | transformers | 7 | 0 | null | text-classification | {"parameters": {"BF16": 72773328897}, "total": 72773328897} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"configuration.json",
"configuration_qwen2_rm.py",
"generation_config.json",
"merges.txt",
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"model-00002-of-00037.safetensors",
"model-00003-of-00037.safetensors",
"model-00004-of-00037.safetensors",
... | 7a21e7fd8426502017457e64f096c620ac048ee7 | [
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"text-classification",
"custom_code",
"en",
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"arxiv:2505.10527",
"base_model:Qwen/WorldPM-72B",
"base_model:finetune:Qwen/WorldPM-72B",
"license:apache-2.0",
... | null | {"architectures": ["Qwen2ForRewardModel"], "auto_map": {"AutoConfig": "configuration_qwen2_rm.Qwen2RMConfig", "AutoModel": "modeling_qwen2_rm.Qwen2ForRewardModel"}, "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != '... | {
"auto_model": "AutoModel",
"custom_class": "modeling_qwen2_rm.Qwen2ForRewardModel",
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/WorldPM-72B"], "datasets": ["openbmb/UltraFeedback"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": "qwen", "license_link": "https://huggingface.co/Qwen/Qwen2.5-WorldPM-72B/blob/main/LICENSE", "metrics": null, "model_name": null,... | # WorldPM-72B-UltraFeedback 🌍
[](https://opensource.org/licenses/Apache-2.0 )
[](https://arxiv.org/abs/2505.10527 )
[![GitHub](https://img.shields.io/badge/GitHub-WorldPM-4b32c3?... | null | [
"apache-2.0",
"qwen",
"https://huggingface.co/Qwen/Qwen2.5-WorldPM-72B/blob/main/LICENSE"
] | [
"openbmb/UltraFeedback"
] | [
"en"
] | 72,773,328,897 | null | null | [
"modeling_qwen2_rm.Qwen2ForRewardModel",
"Qwen2ForRewardModel",
"AutoModel",
"qwen2"
] | [
"feature-extraction",
"text-classification"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
65d685a41be49a8f1cd4411a | 3ade344a5534771a | 99e94b465cd17a5f | 67,996 | WordLevel | null | true | true | false | false | 44 | Lowercase | Split | null | [
"Lowercase"
] | [
"Split"
] | null | 783 | p1atdev/dart-v1-sft | p1atdev | {
"models": [
{
"_id": "65d686ecbbe0ee135d36896d",
"id": "p1atdev/dart-v1-base"
}
],
"relation": "quantized"
} | 1,729 | 171,368 | False | 2024-02-21T23:22:12Z | 2024-03-11T08:02:54Z | transformers | 20 | 0 | null | text-generation | {"parameters": {"BF16": 138851328}, "total": 138851328} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.onnx",
"model.safetensors",
"model_quantized.onnx",
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"special_tokens_map.json",
"tags/character.txt",
"tags/copyright.txt",
"tags/general-explicit.txt",
"tags/general-general.txt",
"tags/genera... | dd5a3f34f3baa15b5266b5f5e2371a97c8ac7702 | [
"transformers",
"onnx",
"safetensors",
"opt",
"text-generation",
"trl",
"sft",
"optimum",
"danbooru",
"dataset:isek-ai/danbooru-tags-2023",
"base_model:p1atdev/dart-v1-base",
"base_model:quantized:p1atdev/dart-v1-base",
"license:apache-2.0",
"text-generation-inference",
"deploy:azure",
... | null | {"architectures": ["OPTForCausalLM"], "model_type": "opt", "tokenizer_config": {"bos_token": "<|bos|>", "eos_token": "<|eos|>", "pad_token": "<|pad|>", "unk_token": "<|unknown|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "p1atdev/dart-v1-base", "datasets": ["isek-ai/danbooru-tags-2023"], "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": ["trl", "sft", "optimum", "da... | # Dart (Danbooru Tags Transformer) v1
This model is a fine-tuned Dart (**Da**nboo**r**u **T**ags Transformer) model that generates danbooru tags.
Demo: [🤗 Space](https://huggingface.co/spaces/p1atdev/danbooru-tags-transformer)
If you are a developer and want to finetune, it's recommended using the base version, [p1... | null | [
"apache-2.0"
] | [
"isek-ai/danbooru-tags-2023"
] | null | 138,851,328 | null | null | [
"OPTForCausalLM",
"AutoModelForCausalLM",
"opt"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6503ca28eda77aafd4bb4b69 | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | joshnguyen/mformer-authority | joshnguyen | null | 100 | 162,136 | False | 2023-09-15T03:06:16Z | 2024-01-11T16:18:27Z | transformers | 2 | 0 | null | text-classification | null | [
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"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
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"en",
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"auto_model": "AutoModelForSequenceClassification",
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"mit"
] | null | [
"en"
] | null | null | null | [
"roberta",
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"RobertaForSequenceClassification"
] | [
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"text"
] | [
"logits"
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65ccd8fd37be1841d078ba8c | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | unsloth/tinyllama-chat-bnb-4bit | unsloth | null | 17,182 | 275,860 | False | 2024-02-14T15:15:09Z | 2024-09-03T03:44:07Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"F32": 101024, "BF16": 131164160, "U8": 999214438}, "total": 1130479622} | [
".gitattributes",
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"special_tokens_map.json",
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"tokenizer.model",
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] | effb5dc8248c9270b0db975639c17084417180a7 | [
"transformers",
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"text-generation",
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"tinyllama",
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"chat",
"conversational",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['co... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "transformers", "tinyllama", "bnb", "chat"]} | # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%... | null | [
"apache-2.0"
] | null | [
"en"
] | 1,130,479,622 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6461d3cf5c46caf4e8a54f89 | 1518b5b91df51a3a | 06c049f6287d7099 | 52,000 | BPE | 51,760 | true | true | true | true | 2 | NFKC | ByteLevel | ByteLevel | [
"NFKC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 604 | cyberagent/open-calm-small | cyberagent | null | 2,088 | 175,487 | False | 2023-05-15T06:40:15Z | 2023-05-18T01:10:33Z | transformers | 20 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 283135bfea85432797ba2500e560af8d0dafd3a8 | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"japanese",
"causal-lm",
"ja",
"dataset:wikipedia",
"dataset:cc100",
"dataset:mc4",
"license:cc-by-sa-4.0",
"text-generation-inference",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|padding|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["wikipedia", "cc100", "mc4"], "eval_results": null, "language": ["ja"], "library_name": null, "license": "cc-by-sa-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["japanese", "causal-lm"], "inference": false} | # OpenCALM-Small
## Model Description
OpenCALM is a suite of decoder-only language models pre-trained on Japanese datasets, developed by CyberAgent, Inc.
## Usage
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("cyberagent/open-calm-s... | null | [
"cc-by-sa-4.0"
] | [
"wikipedia",
"cc100",
"mc4"
] | [
"ja"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6503ca3d52ca06fef947d87e | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | joshnguyen/mformer-care | joshnguyen | null | 92 | 161,939 | False | 2023-09-15T03:06:37Z | 2024-01-11T16:18:10Z | transformers | 2 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 55e9788b7c5b89d69472e91c353982d827c672ea | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"en",
"license:mit",
"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",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | [
"mit"
] | null | [
"en"
] | null | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] | |
63b7ec680d814c2001a024ec | 4b14d08af7ce0075 | 62b8c2882e6b373c | 51,200 | BPE | 50,939 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 577 | sdadas/polish-gpt2-xl | sdadas | null | 1,509 | 164,669 | False | 2023-01-06T09:39:52Z | 2023-04-18T17:54:31Z | transformers | 11 | 0 | null | text-generation | {"parameters": {"F32": 1559939200, "U8": 113246208}, "total": 1673185408} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | fb422d1d1e96eb765bd4dafc5e60d70893c33927 | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"pl",
"license:lgpl",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["pl"], "library_name": null, "license": "lgpl", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | [
"lgpl"
] | null | [
"pl"
] | 1,673,185,408 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] | |
668c7e807dbe0ab21d90bb06 | c1b718d8c9016487 | c81b23e1dcb12302 | 50,280 | BPE | 50,009 | true | true | true | true | 28 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 295 | allenai/OLMo-7B-0724-Instruct-hf | allenai | null | 1,101 | 215,651 | False | 2024-07-09T00:04:16Z | 2024-09-24T16:53:26Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"BF16": 6888095744}, "total": 6888095744} | [
".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_config.json"
] | aba3d33d766a33a44677e3a163f0fe2d1010d90a | [
"transformers",
"safetensors",
"olmo",
"text-generation",
"conversational",
"en",
"dataset:allenai/dolma",
"dataset:allenai/tulu-v2-sft-mixture-olmo-4096",
"dataset:allenai/ultrafeedback_binarized_cleaned",
"arxiv:2402.00838",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["OlmoForCausalLM"], "model_type": "olmo", "tokenizer_config": {"bos_token": null, "eos_token": "<|endoftext|>", "pad_token": "<|padding|>", "unk_token": null, "chat_template": "{{ eos_token }}{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] }}\n{... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["allenai/dolma", "allenai/tulu-v2-sft-mixture-olmo-4096", "allenai/ultrafeedback_binarized_cleaned"], "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"... | <img src="https://allenai.org/olmo/olmo-7b-animation.gif" alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Model Card for OLMo 7B July 2024 Instruct
**Requires transformers versions v4.40.0 or newer**
OLMo is a series of **O**pen **L**anguage **Mo**dels designed to ena... | null | [
"apache-2.0"
] | [
"allenai/dolma",
"allenai/tulu-v2-sft-mixture-olmo-4096",
"allenai/ultrafeedback_binarized_cleaned"
] | [
"en"
] | 6,888,095,744 | null | null | [
"AutoModelForCausalLM",
"OlmoForCausalLM",
"olmo"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
669a12a3dac1eb34c09bbf69 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | amd/AMD-Llama-135m | amd | null | 2,576 | 179,001 | False | 2024-07-19T07:15:47Z | 2024-10-09T01:33:47Z | transformers | 119 | 0 | null | text-generation | {"parameters": {"F32": 134105856}, "total": 134105856} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 9a224a07b9b0210299d8c19b9e694ac56ed3ba1d | [
"transformers",
"safetensors",
"llama",
"text-generation",
"dataset:cerebras/SlimPajama-627B",
"dataset:manu/project_gutenberg",
"arxiv:2204.06745",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["cerebras/SlimPajama-627B", "manu/project_gutenberg"], "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} | # AMD-135m
## Introduction
AMD-Llama-135m is a language model trained on AMD Instinct MI250 accelerators. Based on LLama2 model architecture, this model can be smoothly loaded as LlamaForCausalLM with huggingface transformers. Furthermore, we use the same tokenizer as LLama2, enabling it to be a draft model of specul... | null | [
"apache-2.0"
] | [
"cerebras/SlimPajama-627B",
"manu/project_gutenberg"
] | null | 134,105,856 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66c8bc6fc2db2709dc176353 | 27a47e631d8f9d77 | 377ed779fd867883 | 128,257 | BPE | 280,147 | false | true | true | true | 257 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 224 | fixie-ai/ultravox-v0_4 | fixie-ai | null | 840 | 165,330 | False | 2024-08-23T16:44:31Z | 2025-05-06T23:21:38Z | transformers | 51 | 2 | null | audio-text-to-text | {"parameters": {"BF16": 8072216576}, "total": 8072216576} | [
".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",
"preprocessor_config.json",
"processor_config.js... | 335521c44228935b20fd87e43b4453ae93f30658 | [
"transformers",
"safetensors",
"ultravox",
"feature-extraction",
"audio-text-to-text",
"custom_code",
"en",
"ar",
"de",
"es",
"fr",
"it",
"ja",
"pt",
"ru",
"dataset:fixie-ai/librispeech_asr",
"dataset:fixie-ai/common_voice_17_0",
"dataset:fixie-ai/peoples_speech",
"dataset:fnlp/A... | null | {"architectures": ["UltravoxModel"], "auto_map": {"AutoConfig": "ultravox_config.UltravoxConfig", "AutoModel": "ultravox_model.UltravoxModel", "AutoProcessor": "ultravox_processing.UltravoxProcessor"}, "model_type": "ultravox", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{... | {
"auto_model": "AutoModel",
"custom_class": "ultravox_model.UltravoxModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": null, "datasets": ["fixie-ai/librispeech_asr", "fixie-ai/common_voice_17_0", "fixie-ai/peoples_speech", "fnlp/AnyInstruct"], "eval_results": null, "language": ["en", "ar", "de", "es", "fr", "it", "ja", "pt", "ru"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": nu... | # Model Card for Ultravox
Ultravox is a multimodal Speech LLM built around a pretrained [Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) and [Whisper-medium](https://huggingface.co/openai/whisper-medium) backbone.
See https://ultravox.ai for the GitHub repo and more information.
## Model ... | null | [
"mit"
] | [
"fixie-ai/librispeech_asr",
"fixie-ai/common_voice_17_0",
"fixie-ai/peoples_speech",
"fnlp/AnyInstruct"
] | [
"en",
"ar",
"de",
"es",
"fr",
"it",
"ja",
"pt",
"ru"
] | 8,072,216,576 | null | [
"bleu"
] | [
"AutoModel",
"UltravoxModel",
"ultravox",
"ultravox_model.UltravoxModel"
] | [
"feature-extraction",
"audio-text-to-text"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
65b879b18237bf70e455006d | e54582e7e5bc56b0 | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 688 | yunconglong/DARE_TIES_13B | yunconglong | null | 11,695 | 216,135 | False | 2024-01-30T04:23:13Z | 2024-01-30T04:51:04Z | transformers | 10 | 0 | null | text-generation | {"parameters": {"BF16": 12879138816}, "total": 12879138816} | [
".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_config.json"
] | 74c6e4fbd272c9d897e8c93ee7de8a234f61900f | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"dare ties",
"arxiv:2311.03099",
"arxiv:2306.01708",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"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": ["other"], "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["dare ties"]} | # DARE_TIES_13B
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [yunconglong/Truthful_DPO_... | null | [
"other"
] | null | null | 12,879,138,816 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
639986030544e39696db3e2b | 47849a42819475fc | 8ff860bdec06f4b3 | 28,896 | BPE | 28,639 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 784 | stanford-crfm/BioMedLM | stanford-crfm | null | 7,768 | 243,530 | False | 2022-12-14T08:14:59Z | 2024-03-28T13:57:14Z | transformers | 452 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 3e1a0abb814b8398bc34b4b6680ecf2c26d6a66f | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"dataset:pubmed",
"arxiv:2403.18421",
"license:bigscience-bloom-rail-1.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["pubmed"], "eval_results": null, "language": null, "library_name": null, "license": "bigscience-bloom-rail-1.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "Photosynthesis is"}]} | # Model Card for BioMedLM 2.7B
Note: This model was previously known as PubMedGPT 2.7B, but we have changed it due to a request from the NIH which holds the trademark for "PubMed".
Paper: [BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text](https://arxiv.org/abs/2403.18421)
BioMedLM 2.7B is new lan... | null | [
"bigscience-bloom-rail-1.0"
] | [
"pubmed"
] | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6756f8edb8dae5992db3d03c | 5ee61326abb838a8 | de506a080474956b | 256,000 | BPE | 617,759 | false | true | true | true | 135 | null | Metaspace | Sequence | null | [
"Metaspace"
] | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 785 | BSC-LT/ALIA-40b | BSC-LT | null | 168 | 449,308 | False | 2024-12-09T14:04:29Z | 2025-10-22T14:25:36Z | transformers | 88 | 0 | null | text-generation | {"parameters": {"BF16": 40433885184}, "total": 40433885184} | [
".gitattributes",
"README.md",
"Release note v0.9.md",
"config.json",
"generation_config.json",
"images/LongContext_eval.png",
"images/corpus_languages.png",
"images/logo_alia_2.png",
"images/salamandra_header.png",
"model-00001-of-00017.safetensors",
"model-00002-of-00017.safetensors",
"model... | 27c274f8e88f00275adedb1a60e53039b0f99324 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"bg",
"ca",
"code",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"eu",
"fi",
"fr",
"ga",
"gl",
"hr",
"hu",
"it",
"lt",
"lv",
"mt",
"nl",
"nn",
"oc",
"pl",
"pt",
"ro",
"ru",
"sh",
"sk",
... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["oscar-corpus/colossal-oscar-1.0", "HuggingFaceFW/fineweb-edu", "joelniklaus/eurlex_resources", "joelniklaus/legal-mc4", "projecte-aina/CATalog", "UFRGS/brwac", "community-datasets/hrwac", "danish-foundation-models/danish-gigaword", "HiTZ/euscrawl", "PleIAs/French-PD-Newspapers", "PleI... | 
> [!WARNING]
> **WARNING:** This is a base language model that has not undergone instruction tuning or alignment with human preferences. As a result, it may generate outputs that are inappropriate, misleading, biased, or unsafe. These risks can be mitigated through additional post-trainin... | null | [
"apache-2.0"
] | [
"oscar-corpus/colossal-oscar-1.0",
"HuggingFaceFW/fineweb-edu",
"joelniklaus/eurlex_resources",
"joelniklaus/legal-mc4",
"projecte-aina/CATalog",
"UFRGS/brwac",
"community-datasets/hrwac",
"danish-foundation-models/danish-gigaword",
"HiTZ/euscrawl",
"PleIAs/French-PD-Newspapers",
"PleIAs/French-... | [
"bg",
"ca",
"code",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"eu",
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"sh",
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"uk"
] | 40,433,885,184 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
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"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 171 | michaelfeil/colpali-v12-random-testing | michaelfeil | null | 4,935 | 194,826 | False | 2024-10-08T23:06:46Z | 2024-10-09T00:07:47Z | transformers | 1 | 0 | null | null | {"parameters": {"F16": 8420384}, "total": 8420384} | [
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"paligemma",
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] | null | {"architectures": ["ColPali"], "model_type": "paligemma", "processor_config": {"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_excepti... | {
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<!-- 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 | 8,420,384 | null | null | [
"ColPali",
"paligemma"
] | [
null
] | null | null | null |
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"id": "Qwen/Qwen2-VL-2B-Instruct"
}
],
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} | 4,215 | 185,794 | False | 2024-11-29T10:25:50Z | 2025-03-09T05:44:22Z | transformers | 7 | 0 | null | image-text-to-text | {"parameters": {"F32": 135864, "BF16": 887648768, "U8": 1362698386}, "total": 2250483018} | [
".gitattributes",
"README.md",
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] | 2995340fa3f9bdad892c9dcead519b1165acdb14 | [
"transformers",
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"image-text-to-text",
"multimodal",
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"unsloth",
"vision",
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"base_model:Qwen/Qwen2-VL-2B-Instruct",
"base_model:quantized:Qwen/Qwen2-VL-2B-Instruct",
"license:apache... | null | {"architectures": ["Qwen2VLForConditionalGeneration"], "model_type": "qwen2_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 message... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": "Qwen/Qwen2-VL-2B-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", "qwen", "qwen2", ... | ### ***Unsloth's [Dynamic 4-bit Quants](https://unsloth.ai/blog/dynamic-4bit) selectively avoids quantizing certain parameters, greatly improving accuracy while keeping VRAM usage similar to BnB 4-bit.<br>See our full collection of Unsloth quants on [Hugging Face here.](https://huggingface.co/collections/unsloth/unslot... | null | [
"apache-2.0"
] | null | [
"en"
] | 2,250,483,018 | null | null | [
"AutoModelForImageTextToText",
"qwen2_vl",
"Qwen2VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
654b044e32d67f12f88bfb5a | 990a0e9e0e9fdf56 | f8eba2028d01ebaf | 47,957 | BPE | 82,153 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 786 | abhinand/tamil-llama-7b-instruct-v0.1 | abhinand | null | 886 | 165,219 | False | 2023-11-08T03:45:18Z | 2024-03-04T12:55:08Z | transformers | 10 | 0 | [{"name": "tamil-llama-7b-instruct-v0.1", "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": 48.04, "... | text-generation | null | [
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"pytorch_model-00006-of-00007.bin",
"pytorch... | 7571c4b146d92593df670331e50e1843946458a5 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"ta",
"en",
"arxiv:2311.05845",
"license:llama2",
"model-index",
"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"
} | {"language": ["ta", "en"], "license": "llama2", "model-index": [{"name": "tamil-llama-7b-instruct-v0.1", "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_... | # Tamil LLaMA 7B Instruct v0.1
Welcome to the inaugural release of the Tamil LLaMA 7B instruct model – an important step in advancing LLMs for the Tamil language. This model is ready for immediate inference and is also primed for further fine-tuning to cater to your specific NLP tasks.
To dive deep into the developme... | null | [
"llama2"
] | null | [
"ta",
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"ByteLevel"
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} | 27,219 | 1,132,452 | False | 2024-07-29T08:38:09Z | 2024-09-26T07:57:30Z | sentence-transformers | 77 | 0 | [{"name": "ru-en-RoSBERTa", "results": [{"dataset": {"config": "default", "name": "MTEB CEDRClassification (default)", "revision": "c0ba03d058e3e1b2f3fd20518875a4563dd12db4", "split": "test", "type": "ai-forever/cedr-classification"}, "metrics": [{"type": "accuracy", "value": 44.68650371944739, "verified": false}, {"ty... | feature-extraction | {"parameters": {"F32": 403707904}, "total": 403707904} | [
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"base_model:finetune:ai-forever/ruRoberta-large",
"license:mit",
"model-index",
"text-embeddings-inference",
"endpoint... | null | {"architectures": ["RobertaModel"], "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": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": "ai-forever/ruRoberta-large", "language": ["ru", "en"], "license": "mit", "tags": ["mteb", "transformers", "sentence-transformers"], "model-index": [{"name": "ru-en-RoSBERTa", "results": [{"task": {"type": "MultilabelClassification"}, "dataset": {"name": "MTEB CEDRClassification (default)", "type": "ai-f... | # Model Card for ru-en-RoSBERTa
The ru-en-RoSBERTa is a general text embedding model for Russian. The model is based on [ruRoBERTa](https://huggingface.co/ai-forever/ruRoberta-large) and fine-tuned with ~4M pairs of supervised, synthetic and unsupervised data in Russian and English. Tokenizer supports some English tok... | null | [
"mit"
] | null | [
"ru",
"en"
] | 403,707,904 | null | null | [
"roberta",
"AutoModel",
"RobertaModel"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
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"ByteLevel"
] | [
"ByteLevel"
] | 788 | w11wo/javanese-gpt2-small-imdb | w11wo | null | 22 | 160,334 | False | 2022-03-02T23:29:05Z | 2023-09-14T02:59:51Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"F32": 124439808, "U8": 12582912}, "total": 137022720} | [
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"README.md",
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"tokenizer.json",
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"pytorch",
"tf",
"jax",
"safetensors",
"gpt2",
"text-generation",
"javanese-gpt2-small-imdb",
"jv",
"dataset:w11wo/imdb-javanese",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["w11wo/imdb-javanese"], "eval_results": null, "language": "jv", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["javanese-gpt2-small-imdb"], "widget": [{"text": "Train to Busan yaiku... | ## Javanese GPT-2 Small IMDB
Javanese GPT-2 Small IMDB is a causal language model based on the [GPT-2 model](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf). It was trained on Javanese IMDB movie reviews.
The model was originally the pretrained [Javanese GPT-2 Sma... | null | [
"mit"
] | [
"w11wo/imdb-javanese"
] | [
"jv"
] | 137,022,720 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 172 | OpenGVLab/InternVL3-2B-Instruct | OpenGVLab | {
"models": [
{
"_id": "6800b1b125243877293e4466",
"id": "OpenGVLab/InternVL3-2B-Pretrained"
}
],
"relation": "finetune"
} | 2,358 | 177,243 | False | 2025-04-16T11:22:00Z | 2025-09-11T12:49:19Z | transformers | 7 | 0 | null | image-text-to-text | {"parameters": {"BF16": 2088957440}, "total": 2088957440} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
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"conversation.py",
"examples/image1.jpg",
"examples/image2.jpg",
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"merges.txt",
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"model... | f6c7b60375759170fd49f5e9e298e2178485c5ba | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"internvl",
"custom_code",
"image-text-to-text",
"conversational",
"multilingual",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.10442",
"arxiv:2504.10479",
"arxiv:2412.09616",
"base_model:O... | null | {"architectures": ["InternVLChatModel"], "auto_map": {"AutoConfig": "configuration_internvl_chat.InternVLChatConfig", "AutoModel": "modeling_internvl_chat.InternVLChatModel", "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel"}, "model_type": "internvl_chat", "tokenizer_config": {"bos_token": null, "chat... | {
"auto_model": "AutoModel",
"custom_class": "modeling_internvl_chat.InternVLChatModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["OpenGVLab/InternVL3-2B-Pretrained"], "datasets": null, "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "apache-2.0", "license_name": "qwen", "license_link": "https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE", "metrics": null, "model_name"... | # InternVL3-2B-Instruct
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggingface... | null | [
"apache-2.0",
"qwen",
"https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE"
] | null | [
"multilingual"
] | 2,088,957,440 | null | null | [
"AutoModel",
"internvl_chat",
"InternVLChatModel",
"modeling_internvl_chat.InternVLChatModel"
] | [
"image-text-to-text",
"feature-extraction"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text",
"embeddings"
] |
66186c5c4722d2f0ffa39ec3 | 6af99dc4efc84f72 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 789 | ImranzamanML/GEFS-language-detector | ImranzamanML | null | 143 | 160,416 | False | 2024-04-11T23:03:56Z | 2024-05-01T20:41:07Z | transformers | 4 | 0 | null | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
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"pytorch_model.bin",
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"special_tokens_ma... | b726268f7ed67debc48b5ebbd80dfe9aaacc47fb | [
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"xlm-roberta",
"text-classification",
"en",
"de",
"fr",
"es",
"dataset:papluca/language-identification",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["XLMRobertaForSequenceClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": {"__type": "AddedToken", "content": "<mask>", "lstrip": true, "normalized": true, "rstrip": false, "single_word": false}, "pad_token": "... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["papluca/language-identification"], "eval_results": null, "language": ["en", "de", "fr", "es"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": "text-cla... | # German, English, French and Spanish Language Detector
The GEFS-language-detector model outperformed by achieving an impressive F1 score close to 100%. This result significantly exceeds typical benchmarks and underscores the model's accuracy and reliability in identifying languages.
This is a fined tuned model by usi... | null | [
"apache-2.0"
] | [
"papluca/language-identification"
] | [
"en",
"de",
"fr",
"es"
] | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
65f927d69bf1be93f2011fea | e5ae28ff958aa197 | 84a024d6866886f7 | 131,072 | BPE | 308,070 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 790 | hpcai-tech/grok-1 | hpcai-tech | null | 19,512 | 232,934 | False | 2024-03-19T05:51:18Z | 2024-03-28T08:33:30Z | transformers | 77 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"__init__.py",
"config.json",
"configuration_grok1.py",
"modeling_grok1.py",
"modeling_grok1_outputs.py",
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"pytorch_model-00005... | babfc31aa6cffb15aa89202aaa01ac47bd1925a2 | [
"transformers",
"pytorch",
"text-generation",
"custom_code",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["Grok1ModelForCausalLM"], "auto_map": {"AutoConfig": "configuration_grok1.Grok1Config", "AutoModel": "modeling_grok1.Grok1Model", "AutoModelForCausalLM": "modeling_grok1.Grok1ModelForCausalLM"}, "tokenizer_config": {"bos_token": "[BOS]", "eos_token": "[EOS]", "pad_token": "[PAD]", "unk_token": "[UNK]... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_grok1.Grok1ModelForCausalLM",
"pipeline_tag": "text-generation",
"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": "text-generation", "tags": null} | # Grok-1 (PyTorch Version)
This repository contains the model and weights of the **torch version** of Grok-1 open-weights model. You could find a complete example code of using the torch-version Grok-1 in [ColossalAI GitHub Repository](https://github.com/hpcaitech/ColossalAI/tree/main/examples/language/grok-1). We als... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"Grok1ModelForCausalLM",
"modeling_grok1.Grok1ModelForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
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"text"
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681a37d60283c15b17e824b7 | 3ee6071d77c8f6df | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
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] | 791 | mlxha/Qwen3-4B-grpo-medmcqa | mlxha | {
"models": [
{
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"id": "Qwen/Qwen3-4B"
}
],
"relation": "finetune"
} | 96 | 174,756 | False | 2025-05-06T16:24:54Z | 2025-05-12T18:44:14Z | transformers | 2 | 0 | null | text-generation | null | [
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This model is a fine-tuned version of [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) on the [mlxha/medmcqa-grpo](https://huggingface.co/datasets/mlxha/medmcqa-grpo) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
fro... | null | null | [
"mlxha/medmcqa-grpo"
] | null | null | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
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"text-generation"
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"text"
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"text"
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"text"
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"Replace",
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"Fuse",
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] | 197 | TheBloke/Wizard-Vicuna-30B-Uncensored-GPTQ | TheBloke | {
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{
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"id": "QuixiAI/Wizard-Vicuna-30B-Uncensored"
}
],
"relation": "quantized"
} | 9,107 | 379,309 | False | 2023-05-30T03:11:00Z | 2023-09-27T12:44:25Z | transformers | 606 | 0 | null | text-generation | {"parameters": {"F32": 4151040, "I32": 32102154240, "F16": 426789376}, "total": 32533094656} | [
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"4-bit"... | 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... | {
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"pipeline_tag": "text-generation",
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<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<d... | null | [
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"text"
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6366b1ee2d6ba9a4f71bc91e | 160ff155961a6bcb | 95e12a961ee8f7f8 | 197,285 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 532 | l3cube-pune/hindi-sentence-similarity-sbert | l3cube-pune | null | 2,279 | 166,240 | False | 2022-11-05T18:56:46Z | 2023-10-22T07:28:47Z | sentence-transformers | 7 | 0 | null | sentence-similarity | {"parameters": {"I64": 512, "F32": 237556224}, "total": 237556736} | [
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"special_tokens_map.json",
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"sentence-transformers",
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"sentence-similarity",
"transformers",
"hi",
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"license:cc-by-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": "hi", "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarit... | # HindSBERT-STS
This is a HindSBERT model (<a href = 'https://huggingface.co/l3cube-pune/hindi-sentence-bert-nli'> l3cube-pune/hindi-sentence-bert-nli </a>) fine-tuned on the STS dataset. <br>
Released as a part of project MahaNLP : https://github.com/l3cube-pune/MarathiNLP <br>
A multilingual version of this model su... | null | [
"cc-by-4.0"
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"hi"
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"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 171 | google/paligemma2-3b-ft-docci-448 | google | null | 35,879 | 305,866 | manual | 2024-11-21T19:48:35Z | 2024-12-05T12:43:35Z | transformers | 13 | 0 | null | image-text-to-text | {"parameters": {"BF16": 3033127152}, "total": 3033127152} | [
".gitattributes",
"README.md",
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... | null | {"architectures": ["PaliGemmaForConditionalGeneration"], "model_type": "paligemma", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForImageTextToText",
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"gemma"
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"PaliGemmaForConditionalGeneration",
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6698c2e22f9cd07f44c1b494 | afc54afbc3bed616 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
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] | 10ab31fda8589c7f7b2f02f4ce062f5d4d0fdc90 | [
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"token-classification",
"arxiv:1910.09700",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForTokenClassification"], "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": "AutoModelForTokenClassification",
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"pipeline_tag": "token-classification",
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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 | 354,313,219 | null | null | [
"roberta",
"AutoModelForTokenClassification",
"RobertaForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
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"logits"
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63c91b931e3e1bf4a2c298fc | 41a000f2f9024404 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 13 | Hello-SimpleAI/chatgpt-qa-detector-roberta | Hello-SimpleAI | null | 790 | 163,653 | False | 2023-01-19T10:29:39Z | 2023-01-19T11:02:25Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
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] | 25aad95e922d92631f86164642a3db104deee087 | [
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"en",
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"arxiv:2301.07597",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"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",
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"pipeline_tag": "text-classification",
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} | {"base_model": null, "datasets": ["Hello-SimpleAI/HC3"], "eval_results": null, "language": ["en"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": ["chatgpt"]} | # Model Card for `Hello-SimpleAI/chatgpt-qa-detector-roberta`
This model is trained on `question-answer` pairs of **the filtered full-text** from [Hello-SimpleAI/HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3).
More details refer to [arxiv: 2301.07597](https://arxiv.org/abs/2301.07597) and Gtihub project [He... | null | null | [
"Hello-SimpleAI/HC3"
] | [
"en"
] | null | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
672dec7762371d59e703f671 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-Coder-32B | Qwen | {
"models": [
{
"_id": "66e6d09952865ca1e41c6566",
"id": "Qwen/Qwen2.5-32B"
}
],
"relation": "finetune"
} | 44,472 | 295,452 | False | 2024-11-08T10:48:23Z | 2024-11-18T12:54:58Z | transformers | 145 | 2 | null | text-generation | {"parameters": {"BF16": 32763876352}, "total": 32763876352} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
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"model-00004-of-00014.safetensors",
"model-00005-of-00014.safetensors",
"model-00006-of-0... | 2e12b5f7bc878d424d222e224ed40aee564ec45f | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"code",
"qwen",
"qwen-coder",
"codeqwen",
"conversational",
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"base_model:Qwen/Qwen2.5-32B",
"base_model:finetune:Qwen/Qwen2.5-32B",
"license:apache-2.0",
"text-... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a helpful assistant.' ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen2.5-32B"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen2.5-Coder-32B/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-ge... | # Qwen2.5-Coder-32B
## Introduction
Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-Coder brings t... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-Coder-32B/blob/main/LICENSE"
] | null | [
"en"
] | 32,763,876,352 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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643d73838f6f0a641354edd6 | f56392a3c3b561ef | f26f356cd728caa8 | 49,408 | BPE | 48,894 | true | true | true | true | 2 | Sequence | Sequence | ByteLevel | [
"NFC",
"Replace",
"Lowercase"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 7 | Searchium-ai/clip4clip-webvid150k | Searchium-ai | null | 997 | 180,919 | False | 2023-04-17T16:27:47Z | 2024-10-27T14:21:15Z | transformers | 43 | 0 | null | text-to-video | {"parameters": {"I64": 127, "F32": 151277312}, "total": 151277439} | [
".gitattributes",
"Notebooks/GSI_VideoRetrieval-Evaluation.ipynb",
"Notebooks/GSI_VideoRetrieval_VideoEmbedding.ipynb",
"Notebooks/example/34721191.mp4",
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"Notebooks/features/MSRVTT_test_textual_vectors_Cl4Cl_zeroshot.npy",
"Notebooks/f... | d2f89850fec28ac1e5cd27db2f0b76d7491e61ce | [
"transformers",
"pytorch",
"safetensors",
"clip",
"zero-shot-image-classification",
"text",
"vision",
"video",
"text-to-video",
"dataset:HuggingFaceM4/webvid",
"arxiv:2104.08860",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["CLIPModel"], "model_type": "clip", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|startoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "... | {
"auto_model": "AutoModelForZeroShotImageClassification",
"custom_class": null,
"pipeline_tag": "zero-shot-image-classification",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": ["HuggingFaceM4/webvid"], "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-to-video", "tags": ["text", "vision", "video"]} | # Model Card for CLIP4Clip/WebVid-150k
## Model Details
A CLIP4Clip video-text retrieval model trained on a subset of the WebVid dataset.
The model and training method are described in the paper ["Clip4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"](https://arxiv.org/pdf/2104.08860.pdf) by Lou ... | null | null | [
"HuggingFaceM4/webvid"
] | null | 151,277,439 | null | null | [
"AutoModelForZeroShotImageClassification",
"CLIPModel",
"clip"
] | [
"text-to-video",
"zero-shot-image-classification"
] | [
"vision",
"multimodal"
] | [
"text",
"image"
] | [
"logits",
"video"
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"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 793 | RedHatAI/Meta-Llama-3-8B-Instruct-FP8 | RedHatAI | null | 7,385 | 177,503 | False | 2024-04-25T19:13:07Z | 2024-07-18T19:09:19Z | transformers | 24 | 0 | null | text-generation | null | [
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] | c5c6b5700a4178ef1fdae2ae37827382b90eb400 | [
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"conversational",
"en",
"license:llama3",
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"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"quant_method": "fp8"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_he... | {
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "llama3", "license_name": null, "license_link": "https://llama.meta.com/llama3/license/", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["fp8", "vllm"]} | null | null | [
"llama3",
"https://llama.meta.com/llama3/license/"
] | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
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] | [
"text"
] | [
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663864f5c8950692a491fbf7 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | corto-ai/nomic-embed-text-v1 | corto-ai | null | 10,460 | 298,004 | False | 2024-05-06T05:04:53Z | 2024-05-06T05:18:56Z | sentence-transformers | 3 | 0 | [{"name": "epoch_0_model", "results": [{"task": {"type": "Classification"}, "dataset": {"type": "mteb/amazon_counterfactual", "name": "MTEB AmazonCounterfactualClassification (en)", "config": "en", "split": "test", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205"}, "metrics": [{"type": "accuracy", "value": 76.850... | sentence-similarity | {"parameters": {"F32": 136731648}, "total": 136731648} | [
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"nomic_bert",
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"mteb",
"transformers",
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"en",
"arxiv:2402.01613",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compa... | null | {"architectures": ["NomicBertModel"], "auto_map": {"AutoConfig": "configuration_hf_nomic_bert.NomicBertConfig", "AutoModel": "modeling_hf_nomic_bert.NomicBertModel", "AutoModelForMaskedLM": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForPreTraining"}, "model_type": "nomic_bert", "tokenizer_config": {"cls... | {
"auto_model": "AutoModel",
"custom_class": "modeling_hf_nomic_bert.NomicBertModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"language": ["en"], "library_name": "sentence-transformers", "license": "apache-2.0", "pipeline_tag": "sentence-similarity", "tags": ["feature-extraction", "sentence-similarity", "mteb", "transformers", "transformers.js"], "model-index": [{"name": "epoch_0_model", "results": [{"task": {"type": "Classification"}, "data... | # nomic-embed-text-v1: A Reproducible Long Context (8192) Text Embedder
`nomic-embed-text-v1` is 8192 context length text encoder that surpasses OpenAI text-embedding-ada-002 and text-embedding-3-small performance on short and long context tasks.
| Name | SeqLen | MTEB | LoCo |... | null | [
"apache-2.0"
] | null | [
"en"
] | 136,731,648 | null | null | [
"modeling_hf_nomic_bert.NomicBertModel",
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] | [
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"multimodal"
] | [
"text"
] | [
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] |
62c5e2af8272330bc4256c7a | 5afd7d59d2aa5e01 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 125 | aatmasidha/distilbert-base-uncased-finetuned-emotion | aatmasidha | null | 16 | 159,404 | False | 2022-07-06T19:29:51Z | 2022-08-19T09:35:10Z | transformers | 1 | 0 | [{"name": "distilbert-base-uncased-finetuned-emotion", "results": []}] | text-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | null | [
"apache-2.0"
] | null | null | null | null | [
"accuracy",
"f1"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6899c7b833b8a4a0398a0ed2 | 95a664a7711edc0e | 33b390246e15d4c0 | 151,671 | BPE | 151,387 | true | true | true | true | 28 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 794 | YannQi/R-4B | YannQi | {
"models": [
{
"_id": "680da769038897aa905586a7",
"id": "Qwen/Qwen3-4B"
}
],
"relation": "finetune"
} | 62,649 | 411,845 | False | 2025-08-11T10:36:40Z | 2025-09-04T06:11:30Z | transformers | 181 | 0 | null | image-text-to-text | {"parameters": {"BF16": 4819012384}, "total": 4819012384} | [
".gitattributes",
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"base_model:finetune:Qwen/Qwen3-4B",
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] | null | {"auto_map": {"AutoConfig": "configuration_r.RConfig", "AutoModel": "modeling_r.RForConditionalGeneration", "AutoModelForCausalLM": "modeling_r.RForConditionalGeneration"}, "architectures": ["RForConditionalGeneration"], "model_type": "R", "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": ... | {
"auto_model": "AutoModel",
"custom_class": "modeling_r.RForConditionalGeneration",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["Qwen/Qwen3-4B"], "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": null} | # R-4B: Incentivizing General-Purpose Auto-Thinking Capability in MLLMs via Bi-Mode Annealing and Reinforce Learning
[[📚 Arxiv Paper](https://arxiv.org/pdf/2508.21113)] [[🤗 Hugging Face](https://huggingface.co/YannQi/R-4B)] [[🤖️ ModelScope](https://huggingface.co/YannQi/R-4B)] [[💻 Code](https://github.com/yannqi/... | null | [
"apache-2.0"
] | null | [
"en"
] | 4,819,012,384 | null | null | [
"RForConditionalGeneration",
"AutoModel",
"modeling_r.RForConditionalGeneration",
"R"
] | [
"image-text-to-text",
"feature-extraction"
] | [
"multimodal"
] | [
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"image"
] | [
"text",
"embeddings"
] |
657c5acd9eef0925e07cb75f | cb746674b6df8c76 | 2197a67f76159f09 | 32,005 | Unigram | null | true | true | true | true | 8 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 795 | CATIE-AQ/NERmembert-base-3entities | CATIE-AQ | {
"models": [
{
"_id": "621ffdc036468d709f17433f",
"id": "almanach/camembert-base"
}
],
"relation": "finetune"
} | 10 | 159,238 | False | 2023-12-15T13:55:25Z | 2024-11-26T13:23:56Z | transformers | 2 | 0 | [{"name": "NERmembert-base-3entities", "results": []}] | token-classification | {"parameters": {"F32": 110034436}, "total": 110034436} | [
".gitattributes",
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"training... | d35059c87fefb5b0ec9ea7af1e162b224c5ae220 | [
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"arxiv:1910.09700",
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"base_model:finetune:almanach/camembert-base",
"doi:10.57967/hf/1750",
"license:mit",
"co2_eq_emissions",... | null | {"architectures": ["CamembertForTokenClassification"], "model_type": "camembert", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": "camembert-base", "datasets": ["CATIE-AQ/frenchNER_3entities"], "eval_results": [], "language": ["fr"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": "NERmembert-base-3entities", "pipeline_... | # NERmembert-base-3entities
## Model Description
We present **NERmembert-base-3entities**, which is a [CamemBERT base](https://huggingface.co/camembert-base) fine-tuned for the Name Entity Recognition task for the French language on five French NER datasets for 3 entities (LOC, PER, ORG).
All these datasets were co... | null | [
"mit"
] | [
"CATIE-AQ/frenchNER_3entities"
] | [
"fr"
] | 110,034,436 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"CamembertForTokenClassification",
"AutoModelForTokenClassification",
"camembert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
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6318b9dcc5ada0f96330ce61 | b09ab9fd6ed532ef | f26f356cd728caa8 | 49,408 | BPE | 48,894 | true | true | true | true | 2 | Sequence | Sequence | ByteLevel | [
"NFC",
"Replace",
"Lowercase"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 414 | microsoft/xclip-large-patch14-16-frames | microsoft | null | 19 | 159,397 | False | 2022-09-07T15:33:48Z | 2022-09-08T11:09:07Z | transformers | 3 | 0 | [{"name": "nielsr/xclip-large-patch14-16-frames", "results": [{"task": {"type": "video-classification"}, "dataset": {"name": "Kinetics 400", "type": "kinetics-400"}, "metrics": [{"type": "top-1 accuracy", "value": 87.7, "verified": false}, {"type": "top-5 accuracy", "value": 97.4, "verified": false}]}]}] | video-classification | null | [
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} | {"language": "en", "license": "mit", "tags": ["vision", "video-classification"], "model-index": [{"name": "nielsr/xclip-large-patch14-16-frames", "results": [{"task": {"type": "video-classification"}, "dataset": {"name": "Kinetics 400", "type": "kinetics-400"}, "metrics": [{"type": "top-1 accuracy", "value": 87.7, "ver... | # X-CLIP (large-sized model)
X-CLIP model (large-sized, patch resolution of 14) trained fully-supervised on [Kinetics-400](https://www.deepmind.com/open-source/kinetics). It was introduced in the paper [Expanding Language-Image Pretrained Models for General Video Recognition](https://arxiv.org/abs/2208.02816) by Ni e... | null | [
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621ffdc136468d709f17b7ac | 2d0341bd3a73bae6 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
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] | [
"Metaspace"
] | [
"Metaspace"
] | 32 | google/t5-xxl-lm-adapt | google | null | 192 | 160,006 | False | 2022-03-02T23:29:05Z | 2023-01-24T16:52:50Z | transformers | 10 | 0 | null | null | null | [
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"transformers",
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"text-generation-inference",
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] | 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": ["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": ["t5-lm-adapt"]} | [Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) Version 1.1 - LM-Adapted
## Version 1.1 - LM-Adapted
[T5 Version 1.1 - LM Adapted](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#lm-adapted-t511lm100k) includes the follo... | null | [
"apache-2.0"
] | [
"c4"
] | [
"en"
] | null | null | null | [
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"text2text-generation"
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64ca9d0f8174e45ae03a073a | 1e7de54e704f366a | d4959f5e45fb7540 | 32,001 | BPE | 61,249 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 309 | elinas/chronos-13b-v2 | elinas | null | 817 | 163,005 | False | 2023-08-02T18:14:39Z | 2023-10-10T20:36:12Z | transformers | 27 | 0 | null | text-generation | null | [
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"transformers",
"pytorch",
"llama",
"text-generation",
"chatbot",
"storywriting",
"generalist-model",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama"} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["llama", "pytorch", "chatbot", "storywriting", "generalist-model"]} | # chronos-13b-v2
This is the FP16 PyTorch / HF version of **chronos-13b-v2** based on the **LLaMA v2 Base** model.
Only use this version for further quantization or if you would like to run in full precision, as long as you have the VRAM required.
This model is primarily focused on chat, roleplay, storywriting, with... | null | [
"llama2"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64ca3ecdcbf85b57311c23e4 | a3057b3c341dfdaa | 9ebc2e1b24ebcff4 | 32,006 | BPE | 61,249 | true | false | true | true | 9 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 796 | TheBloke/OpenAssistant-Llama2-13B-Orca-v2-8K-3166-GPTQ | TheBloke | {
"models": [
{
"_id": "64c75b4fed521f27a44147a8",
"id": "OpenAssistant/llama2-13b-orca-v2-8k-3166"
}
],
"relation": "quantized"
} | 6 | 158,442 | False | 2023-08-02T11:32:29Z | 2023-09-27T13:00:46Z | transformers | 24 | 0 | null | text-generation | {"parameters": {"F32": 2560, "I32": 12687769600, "F16": 330388480}, "total": 13018160640} | [
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"llama",
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"dataset:nickrosh/Evol-Instruct-Code-80k-v1",
"base_model:OpenAssistant/llama2-13b-orca-v2-8k-3166",
"base_model:quanti... | 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": "OpenAssistant/llama2-13b-orca-v2-8k-3166", "datasets": ["shahules786/orca-chat", "rombodawg/MegaCodeTraining112k", "theblackcat102/evol-codealpaca-v1", "nickrosh/Evol-Instruct-Code-80k-v1"], "eval_results": null, "language": null, "library_name": null, "license": "other", "license_name": null, "license_... | <!-- 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 | [
"other"
] | [
"shahules786/orca-chat",
"rombodawg/MegaCodeTraining112k",
"theblackcat102/evol-codealpaca-v1",
"nickrosh/Evol-Instruct-Code-80k-v1"
] | null | 13,018,160,640 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175efa | c347bb1662d6729b | 47b1b606cb314d14 | 30,000 | Unigram | null | true | true | true | true | 3 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 797 | IlyaGusev/rut5_base_headline_gen_telegram | IlyaGusev | null | 22,763 | 185,735 | False | 2022-03-02T23:29:04Z | 2021-12-18T19:27:52Z | transformers | 9 | 0 | null | summarization | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | 7ee21f469a71b19a107eef60766bba8ad29bdbb7 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"summarization",
"ru",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ru"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["summarization"], "widget": [{"text": "\u041a\u043e\u043c\u0438\u0441\u0441\u043... | # RuT5TelegramHeadlines
## Model description
Based on [rut5-base](https://huggingface.co/cointegrated/rut5-base) model
## Intended uses & limitations
#### How to use
```python
from transformers import AutoTokenizer, T5ForConditionalGeneration
model_name = "IlyaGusev/rut5_base_headline_gen_telegram"
tokenizer = Au... | null | [
"apache-2.0"
] | null | [
"ru"
] | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68ecbe2c9567237a52dbf9a8 | 6a210b8662165fae | 8a779e968e90f215 | 50,370 | BPE | 50,009 | true | true | true | true | 118 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 798 | mixedbread-ai/mxbai-edge-colbert-v0-17m | mixedbread-ai | null | 339,678 | 2,043,929 | False | 2025-10-13T08:54:04Z | 2026-02-14T04:21:12Z | PyLate | 34 | 0 | [{"name": "mxbai-edge-colbert-v0-17m", "results": [{"task": {"type": "py-late-information-retrieval", "name": "Py Late Information Retrieval"}, "dataset": {"name": "NanoClimateFEVER", "type": "NanoClimateFEVER"}, "metrics": [{"type": "MaxSim_accuracy@1", "value": 0.28, "name": "Maxsim Accuracy@1", "verified": false}, {... | sentence-similarity | {"parameters": {"F32": 16797952}, "total": 16797952} | [
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"e... | null | {"architectures": ["ModernBertModel"], "model_type": "modernbert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[MASK]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
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"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"language": ["en"], "library_name": "PyLate", "license": "apache-2.0", "metrics": ["MaxSim_accuracy@1", "MaxSim_accuracy@3", "MaxSim_accuracy@5", "MaxSim_accuracy@10", "MaxSim_precision@1", "MaxSim_precision@3", "MaxSim_precision@5", "MaxSim_precision@10", "MaxSim_recall@1", "MaxSim_recall@3", "MaxSim_recall@5", "MaxS... | null | null | [
"apache-2.0"
] | null | [
"en"
] | 16,797,952 | null | [
"MaxSim_accuracy@1",
"MaxSim_accuracy@3",
"MaxSim_accuracy@5",
"MaxSim_accuracy@10",
"MaxSim_precision@1",
"MaxSim_precision@3",
"MaxSim_precision@5",
"MaxSim_precision@10",
"MaxSim_recall@1",
"MaxSim_recall@3",
"MaxSim_recall@5",
"MaxSim_recall@10",
"MaxSim_ndcg@10",
"MaxSim_mrr@10",
"M... | [
"AutoModel",
"ModernBertModel",
"modernbert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
64ec954ac2bcaa4525fb4ce3 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | elyza/ELYZA-japanese-Llama-2-7b | elyza | null | 1,064 | 165,362 | False | 2023-08-28T12:38:34Z | 2023-08-29T03:45:51Z | transformers | 96 | 0 | null | text-generation | null | [
".gitattributes",
"LICENCE.txt",
"README.md",
"config.json",
"generation_config.json",
"key_visual.png",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.j... | 976887c5891284db204320860bb84b71d598063e | [
"transformers",
"pytorch",
"llama",
"text-generation",
"ja",
"en",
"arxiv:2307.09288",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": false, "rstrip... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ja", "en"], "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | ## ELYZA-japanese-Llama-2-7b
### Model Description
**ELYZA-japanese-Llama-2-7b** は、 Llama2をベースとして日本語能力を拡張するために追加事前学習を行ったモデルです。
詳細は [Blog記事](https://note.com/elyza/n/na405acaca130) を参照してください。
### Usage
```python
import torch
from transformers import AutoModelForCausa... | null | [
"llama2"
] | null | [
"ja",
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6476cef526ec66674c7055cf | 8bc6b61a7b6c29c2 | 4c6e091e8dffb5aa | 30,003 | BPE | 29,740 | false | true | true | true | 7 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 299 | beomi/polyglot-ko-12.8b-safetensors | beomi | null | 67 | 158,244 | False | 2023-05-31T04:37:09Z | 2023-05-31T05:22:04Z | transformers | 5 | 0 | null | text-generation | {"parameters": {"F16": 12893603840, "F32": 1280, "BOOL": 167772160}, "total": 13061377280} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00028.safetensors",
"model-00002-of-00028.safetensors",
"model-00003-of-00028.safetensors",
"model-00004-of-00028.safetensors",
"model-00005-of-00028.safetensors",
"model-00006-of-00028.safetensors",
"model-0... | 62f1244d869916e1d0b91027df669124c2fda9ec | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"polyglot-ko",
"ko",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ko"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["polyglot-ko"]} | # beomi/polyglot-ko-12.8b-safetensors (fp16)
Original pytorch weight(fp16): [EleutherAI/polyglot-ko-12.8b](https://huggingface.co/EleutherAI/polyglot-ko-12.8b)
This repo contains converted Polyglot-ko 12.8B Model with
- Safetensors format with Smaller shard size(1GB) | null | [
"apache-2.0"
] | null | [
"ko"
] | 13,061,377,280 | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 434 | google/gemma-3-27b-pt | google | null | 16,158 | 263,697 | manual | 2025-03-01T19:10:03Z | 2025-03-21T17:18:09Z | transformers | 123 | 0 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model-00001-of-00012.safetensors",
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"model-00004-of-00012.safetensors",
"model-00005-of-00012.safetensors",
"model-00006-of-00012.s... | 9fe3c4ebc93fbadb14913801536d022054ef11cc | [
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"arxiv:1903.00161",
"arxiv:2009.03300",
"arxiv:2304.06364",
"arxiv:2103.03874",
"ar... | null | {"architectures": ["Gemma3ForConditionalGeneration"], "model_type": "gemma3", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null, "extra_gated_heading": "Access Gemma on Hugging Face", "... | null | null | [
"gemma"
] | null | null | null | null | null | [
"AutoModelForImageTextToText",
"Gemma3ForConditionalGeneration",
"gemma3"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
65d62c8ed1f00c5f97b996bd | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 106 | unsloth/gemma-7b-bnb-4bit | unsloth | null | 653 | 162,977 | False | 2024-02-21T17:02:06Z | 2025-06-02T22:28:11Z | transformers | 18 | 0 | null | text-generation | {"parameters": {"F32": 526400, "BF16": 786607104, "U8": 7993362736}, "total": 8780496240} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 1eee0c076e000bb00794d0c86227c3439e448ad1 | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"unsloth",
"gemma-7b",
"bnb",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "transformers", "gemma", "gemma-7b", "bnb"]} | # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
We have a Google Colab Tesla T4 notebook for Gemma 7b here: https://colab.research.google.com/drive/10NbwlsRChbma1v55m8LAPYG15uQv6HLo?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.p... | null | [
"apache-2.0"
] | null | [
"en"
] | 8,780,496,240 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67b50abaa64445f58c6621d8 | 2cdba62b0ecdc386 | c0d8706e90709d09 | 49,155 | BPE | 48,872 | false | true | false | true | 41 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 588 | modularStarEncoder/ModularStarEncoder | modularStarEncoder | null | 49 | 180,406 | False | 2025-02-18T22:33:30Z | 2025-05-22T12:15:11Z | transformers | 2 | 0 | null | feature-extraction | {"parameters": {"BF16": 1104091214}, "total": 1104091214} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"config.py",
"merges.txt",
"model.safetensors",
"modularStarEncoder.py",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 55b8daf50908a6ec60e77534e8579b2d13837c58 | [
"transformers",
"safetensors",
"ModularStarEncoder",
"feature-extraction",
"custom_code",
"dataset:bigcode/the-stack-v2-train-full-ids",
"arxiv:2503.03008",
"arxiv:2307.16885",
"license:bigcode-openrail-m",
"region:us"
] | null | {"architectures": ["ModularStarEncoder"], "auto_map": {"AutoConfig": "config.ModularStarEncoderConfig", "AutoModel": "modularStarEncoder.ModularStarEncoder"}, "model_type": "ModularStarEncoder", "tokenizer_config": {"bos_token": "<|endoftext|>", "cls_token": "<cls>", "eos_token": "<|endoftext|>", "mask_token": "<mask>"... | {
"auto_model": "AutoModel",
"custom_class": "modularStarEncoder.ModularStarEncoder",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": null, "datasets": ["bigcode/the-stack-v2-train-full-ids"], "eval_results": null, "language": null, "library_name": "transformers", "license": "bigcode-openrail-m", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ModularStarEncoder-1B Pre-trained model
<!-- Provide a quick summary of what the model is/does. -->
ModularStarEncoder-1B (MoSE) is an encoder pre-trained on [The Stack v2](https://huggingface.co/datasets/bigcode/the-stack-v2-train).
ModularStarEncoder is a modular pre-trained encoder with five exit points, allowi... | null | [
"bigcode-openrail-m"
] | [
"bigcode/the-stack-v2-train-full-ids"
] | null | 1,104,091,214 | null | null | [
"modularStarEncoder.ModularStarEncoder",
"ModularStarEncoder",
"AutoModel"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
657eaaabefc0f84bcb888d23 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | rishiraj/CatPPT-base | rishiraj | null | 2,803 | 173,224 | False | 2023-12-17T08:00:43Z | 2024-01-10T18:34:48Z | transformers | 48 | 0 | null | text-generation | {"parameters": {"F16": 7241732096}, "total": 7241732096} | [
".gitattributes",
"README.md",
"config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 2f73ffc6b55b7bc3e0a1cc6fa613ee948c9484c4 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"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": ["merge"]} | # 😼 CatPPT
Introducing "CatPPT" - the purrfect alternative to that other big cat in town, known for keeping all the secrets to itself! Our feline friend here is created through merging openchat and neuralchat models using Gradient SLERP method (resulting in [rishiraj/CatPPT-base](https://huggingface.co/rishiraj/CatPP... | null | [
"apache-2.0"
] | null | null | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65262788e0094b7bf223ace9 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | royallab/ZephRP-m7b | royallab | null | 12,031 | 214,911 | False | 2023-10-11T04:41:44Z | 2023-10-12T02:37:42Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 4ef26ff937765b3fb279151ba9af48fb42c03932 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"en",
"license:cc-by-nc-4.0",
"text-generation-inference",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "</s>", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["mistral"], "inference": false} | # ZephRP-m7b
This is a [Mistral](https://huggingface.co/mistralai/Mistral-7B-v0.1)-based model consisting of a merge between [HuggingFaceH4/zephyr-7b-alpha](https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha) and PEFT adapter trained using the LimaRP dataset.
The goal was to combine the message length instruction t... | null | [
"cc-by-nc-4.0"
] | null | [
"en"
] | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f178765 | 71140a663949f258 | 8a01c02d4d0a401c | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 9 | airesearch/bert-base-multilingual-cased-finetune-qa | airesearch | null | 3 | 157,467 | False | 2022-03-02T23:29:05Z | 2021-07-14T05:50:52Z | transformers | 0 | 0 | null | question-answering | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | e77e3864b649bacb6cca5a550fde234b5ed2f722 | [
"transformers",
"pytorch",
"bert",
"question-answering",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForQuestionAnswering"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "\u0e2a\u0e27\u0e19\u0e01\u0e38\u0e2b\u0e25\u0e32\u0e1a\u0e40\u0e... | # bert-base-multilingual-cased
Finetuning `bert-base-multilingual-cased` with the training set of `iapp_wiki_qa_squad`, `thaiqa_squad`, and `nsc_qa` (removed examples which have cosine similarity with validation and test examples over 0.8; contexts of the latter two are trimmed to be around 300 `newmm` words). Benchm... | null | null | null | null | null | null | null | [
"AutoModelForQuestionAnswering",
"bert",
"BertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17e8ff | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large | nreimers | null | 1,008 | 159,619 | False | 2022-03-02T23:29:05Z | 2021-06-20T19:03:02Z | transformers | 18 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 160deb78aca30f63754e512a93337ce8013a32ca | [
"transformers",
"pytorch",
"xlm-roberta",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaForMaskedLM"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normali... | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | # MiniLMv2
This is a MiniLMv2 model from: [https://github.com/microsoft/unilm](https://github.com/microsoft/unilm/tree/master/minilm) | null | null | null | null | null | null | null | [
"AutoModelForMaskedLM",
"xlm-roberta",
"XLMRobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
67b3bdb37991efe21b3e1551 | 897e472a76b74290 | ca60ee72fe371096 | 49,155 | BPE | 48,891 | false | true | true | true | 22 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 367 | ibm-granite/granite-3.2-2b-instruct | ibm-granite | {
"models": [
{
"_id": "6753571bc050f63baedf520f",
"id": "ibm-granite/granite-3.1-2b-instruct"
}
],
"relation": "finetune"
} | 4,641 | 182,213 | False | 2025-02-17T22:52:35Z | 2025-04-17T11:39:08Z | transformers | 53 | 0 | null | text-generation | {"parameters": {"BF16": 2533531648}, "total": 2533531648} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json... | 641593c3b25bec0b1efe9f0f7d7a67f7243f86a3 | [
"transformers",
"safetensors",
"granite",
"text-generation",
"language",
"granite-3.2",
"conversational",
"arxiv:0000.00000",
"base_model:ibm-granite/granite-3.1-2b-instruct",
"base_model:finetune:ibm-granite/granite-3.1-2b-instruct",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["GraniteForCausalLM"], "model_type": "granite", "tokenizer_config": {"bos_token": "<|end_of_text|>", "chat_template": "{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content'] %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["ibm-granite/granite-3.1-2b-instruct"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["language", "granite-3.2... | # Granite-3.2-2B-Instruct
**Model Summary:**
Granite-3.2-2B-Instruct is an 2-billion-parameter, long-context AI model fine-tuned for thinking capabilities. Built on top of [Granite-3.1-2B-Instruct](https://huggingface.co/ibm-granite/granite-3.1-2b-instruct), it has been trained using a mix of permissively licensed ope... | null | [
"apache-2.0"
] | null | null | 2,533,531,648 | null | null | [
"granite",
"AutoModelForCausalLM",
"GraniteForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66c3bba8ddb17e853c66b70e | 21feada71fab2765 | 12ebeebff692ebb1 | 131,072 | BPE | 269,443 | false | true | true | true | 1,000 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 245 | nvidia/Mistral-NeMo-Minitron-8B-Base | nvidia | null | 3,231 | 171,636 | False | 2024-08-19T21:39:52Z | 2024-08-22T06:47:48Z | transformers | 177 | 0 | null | text-generation | {"parameters": {"BF16": 8414105600}, "total": 8414105600} | [
".gitattributes",
"NOTICE",
"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",
"nemo/mistral-nemo-minitron-8b-base.ne... | cc94637b669b62c4829b1e0c3b9074fecd883b74 | [
"transformers",
"nemo",
"safetensors",
"mistral",
"text-generation",
"arxiv:2408.11796",
"arxiv:2009.03300",
"arxiv:2407.14679",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "other", "license_name": "nvidia-open-model-license", "license_link": "https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf", "metrics": null, "model_name... | # Mistral-NeMo-Minitron-8B-Base
## Model Overview
Mistral-NeMo-Minitron-8B-Base is a base text-to-text model that can be adopted for a variety of natural language generation tasks. It is a large language model (LLM) obtained by pruning and distilling the Mistral-NeMo 12B; specifically, we prune the embedding dimensio... | null | [
"other",
"nvidia-open-model-license",
"https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf"
] | null | null | 8,414,105,600 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6673a66721bc4bc41d9fe6f4 | 39b1e434a495263c | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 349 | WillHeld/DiVA-llama-3-v0-8b | WillHeld | {
"models": [
{
"_id": "6698d8a0653e4babe21e1e7d",
"id": "meta-llama/Llama-3.1-8B-Instruct"
}
],
"relation": "finetune"
} | 65 | 157,849 | False | 2024-06-20T03:47:51Z | 2024-12-19T21:26:18Z | transformers | 35 | 0 | null | feature-extraction | {"parameters": {"F32": 2486915072}, "total": 2486915072} | [
".gitattributes",
"LICENSE",
"README.md",
"__init__.py",
"config.json",
"configuring_diva.py",
"model.safetensors",
"model.safetensors.index.json",
"modeling_diva.py",
"preprocessor_config.json",
"special_tokens_map.json",
"test.py",
"tokenizer.json",
"tokenizer_config.json"
] | 6e761b15ebde6ccf9b9e91d47a4ae42d79c066ca | [
"transformers",
"safetensors",
"diva",
"feature-extraction",
"custom_code",
"dataset:mozilla-foundation/common_voice_17_0",
"arxiv:2410.02678",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"license:mpl-2.0",
"region:us"
] | null | {"model_type": "diva", "architectures": ["DiVAModel"], "auto_map": {"AutoConfig": "configuring_diva.DiVAConfig", "AutoModel": "modeling_diva.DiVAModel"}, "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start... | {
"auto_model": "AutoModel",
"custom_class": "modeling_diva.DiVAModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["meta-llama/Llama-3.1-8B-Instruct"], "datasets": ["mozilla-foundation/common_voice_17_0"], "eval_results": null, "language": null, "library_name": null, "license": "mpl-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Model Card for Diva Llama 3
<!-- Provide a quick summary of what the model is/does. [Optional] -->
This is an end-to-end Voice Assistant Model which can handle speech and text as inputs. It is trained using distillation loss. More details in the [pre-print](https://arxiv.org/abs/2410.02678) here.
See the model in a... | null | [
"mpl-2.0"
] | [
"mozilla-foundation/common_voice_17_0"
] | null | 2,486,915,072 | null | null | [
"modeling_diva.DiVAModel",
"AutoModel",
"diva",
"DiVAModel"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
621ffdc136468d709f17d200 | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | kiri-ai/t5-base-qa-summary-emotion | kiri-ai | null | 434 | 248,192 | False | 2022-03-02T23:29:05Z | 2021-09-22T08:55:00Z | transformers | 8 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"pytorch_model_quantized.bin",
"spiece.model",
"tokenizer.json"
] | 66b7d2e5273b4fd4fff90c366702b71a857e5801 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"question-answering",
"emotion-detection",
"summarisation",
"en",
"dataset:coqa",
"dataset:squad_v2",
"dataset:go_emotions",
"dataset:cnn_dailymail",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"reg... | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5"} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["coqa", "squad_v2", "go_emotions", "cnn_dailymail"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["f1"], "model_name": null, "pipeline_tag": "text2text-generation", "tags": ["question-an... | # T5 Base with QA + Summary + Emotion
## Dependencies
Requires transformers>=4.0.0
## Description
This model was finetuned on the CoQa, Squad 2, GoEmotions and CNN/DailyMail.
It achieves a score of **F1 79.5** on the Squad 2 dev set and a score of **F1 70.6** on the CoQa dev set.
Summarisation and emotion detecti... | null | [
"apache-2.0"
] | [
"coqa",
"squad_v2",
"go_emotions",
"cnn_dailymail"
] | [
"en"
] | null | null | [
"f1"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"question-answering",
"text2text-generation",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6503ca56453165de0b886e06 | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | joshnguyen/mformer-loyalty | joshnguyen | null | 82 | 157,380 | False | 2023-09-15T03:07:02Z | 2024-01-11T16:17:45Z | transformers | 2 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 7417251a03402928c202a467aa1c68e976056c69 | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"en",
"license:mit",
"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",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | [
"mit"
] | null | [
"en"
] | null | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] | |
66715f7bce36cc6c6258031b | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | instruction-pretrain/finance-Llama3-8B | instruction-pretrain | null | 5,225 | 173,863 | False | 2024-06-18T10:20:43Z | 2026-03-02T08:23:22Z | transformers | 75 | 0 | null | text-generation | {"parameters": {"F32": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00007.safetensors",
"model-00002-of-00007.safetensors",
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"model-00004-of-00007.safetensors",
"model-00005-of-00007.safetensors",
"model-00006-of-00007.safetensors",
"model-0... | 49a6be686e9f3d0f910f5d092b0d98b087361bd8 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"finance",
"en",
"dataset:Open-Orca/OpenOrca",
"dataset:GAIR/lima",
"dataset:WizardLM/WizardLM_evol_instruct_V2_196k",
"arxiv:2406.14491",
"arxiv:2601.16206",
"arxiv:2309.09530",
"license:llama3",
"text-generation-inference",
"en... | 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": null, "datasets": ["Open-Orca/OpenOrca", "GAIR/lima", "WizardLM/WizardLM_evol_instruct_V2_196k"], "eval_results": null, "language": ["en"], "library_name": null, "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finance"]... | # Instruction Pre-Training: Language Models are Supervised Multitask Learners (EMNLP 2024)
This repo contains the **finance model developed from Llama3-8B** in our paper [Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://huggingface.co/papers/2406.14491).
We explore supervised multit... | null | [
"llama3"
] | [
"Open-Orca/OpenOrca",
"GAIR/lima",
"WizardLM/WizardLM_evol_instruct_V2_196k"
] | [
"en"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6503ca4a61073423437baaa2 | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | joshnguyen/mformer-fairness | joshnguyen | null | 94 | 157,159 | False | 2023-09-15T03:06:50Z | 2024-01-11T16:17:58Z | transformers | 3 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
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MMLW (muszę mieć lepszą wiadomość) are neural text encoders for Polish.
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# Model Card for StarChat2 15B
StarChat is a series of language models that are trained to act as helpful coding assistan... | null | null | [
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should probably proofread and complete it, then remove this comment. -->
# FineMath classifier
## Model summary
This is a classifier for evaluating mathematical reasoning and deduction in web pages, fine-... | null | [
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"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
65a3f3bf60cc6b04c99a3edf | 3bb1bb2b6ba4e4e5 | c2bcd4c1aacf5b89 | 130,000 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 804 | upskyy/kf-deberta-multitask | upskyy | null | 199 | 261,211 | False | 2024-01-14T14:46:23Z | 2024-01-15T01:32:03Z | sentence-transformers | 17 | 0 | null | sentence-similarity | {"parameters": {"F32": 185290752}, "total": 185290752} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"eval/similarity_evaluation_sts-dev_results.csv",
"model.safetensors",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"similarity_evaluation_sts-test_results.csv",
"sp... | a0910cb1c7c87df5f5f68f874ccfa87520a87fc1 | [
"sentence-transformers",
"pytorch",
"safetensors",
"deberta-v2",
"feature-extraction",
"sentence-similarity",
"transformers",
"ko",
"arxiv:2004.03289",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DebertaV2Model"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "ko", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "tr... | # kf-deberta-multitask
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. You can check the training recipes on [GitHub](https://github.com/upskyy/kf-deberta-multitask).
<!... | null | null | null | [
"ko"
] | 185,290,752 | null | null | [
"DebertaV2Model",
"AutoModel",
"deberta-v2"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
65d6312ddbfd082b5e4c73d3 | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 106 | unsloth/gemma-2b-bnb-4bit | unsloth | null | 2,487 | 172,422 | False | 2024-02-21T17:21:49Z | 2024-09-03T03:44:46Z | transformers | 16 | 0 | null | text-generation | {"parameters": {"F32": 155232, "BF16": 524363776, "U8": 2043783314}, "total": 2568302322} | [
".gitattributes",
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"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | ee801bdc9451d4427d251f6377f5df1f67785e19 | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"unsloth",
"gemma-2b",
"bnb",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "transformers", "gemma", "gemma-2b", "bnb"]} | # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
We have a Google Colab Tesla T4 notebook for Gemma 2b here: https://colab.research.google.com/drive/15gGm7x_jTm017_Ic8e317tdIpDG53Mtu?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.p... | null | [
"apache-2.0"
] | null | [
"en"
] | 2,568,302,322 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
653835689c474315d7322f27 | 6d48427baa022d42 | ffae8233e53a99e4 | 256,204 | BPE | 514,098 | true | true | true | true | 207 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 805 | cointegrated/SONAR_200_text_encoder | cointegrated | null | 833 | 172,096 | False | 2023-10-24T21:21:44Z | 2024-11-08T16:27:21Z | transformers | 10 | 0 | null | sentence-similarity | {"parameters": {"F32": 766091264}, "total": 766091264} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 29f2eac73636d1548c2cb227dbfb2772b31ebc4f | [
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"azb",
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"bjn",... | null | {"architectures": ["M2M100Encoder"], "model_type": "m2m_100", "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": "M2M100Encoder",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ace", "ace", "acm", "acq", "aeb", "af", "ajp", "ak", "am", "apc", "ar", "ars", "ary", "arz", "as", "ast", "awa", "ay", "azb", "azj", "ba", "bm", "ban", "be", "bem", "bn", "bho", "bjn", "bjn", "bo", "bs", "bug", "bg", "ca", "ceb", "cs", "cjk", "c... | This is a port of the multilingual SONAR text encoder (https://huggingface.co/facebook/SONAR) to the `transformers` format from `fairseq2`.
Its embeddings are expected be equal to those the official implementation (https://github.com/facebookresearch/SONAR), but the latter stays the source of truth.
The encoder suppo... | null | [
"cc-by-nc-4.0"
] | null | [
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"bjn",
"bo",
"bs",
"bug",
"bg",
"ca",
"ceb",
"cs",
"cjk",
... | 766,091,264 | null | null | [
"m2m_100",
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] | [
null,
"sentence-similarity"
] | [
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] | [
"text"
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"logits"
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"Punctuation",
"ByteLevel",
"Digits",
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] | [
"ByteLevel"
] | 45 | TheBloke/Falcon-180B-Chat-GPTQ | TheBloke | {
"models": [
{
"_id": "64f5957cab97f9a83ecb71ee",
"id": "tiiuae/falcon-180B-chat"
}
],
"relation": "quantized"
} | 48 | 156,031 | False | 2023-09-06T16:47:56Z | 2023-09-27T13:02:37Z | transformers | 70 | 0 | null | text-generation | null | [
".gitattributes",
"ACCEPTABLE_USE_POLICY.txt",
"LICENSE.txt",
"README.md",
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"model-00005-of-00010.safetensors",
... | f764ba0954ebea9c899af9279090f1ba1f349ceb | [
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"arxiv:2205.14135",
"arxiv:2306.01116",
"base_model:tiiuae/falcon-180B-chat",
"base_model:quantized:tiiuae... | null | {"architectures": ["FalconForCausalLM"], "model_type": "falcon", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "tiiuae/falcon-180B-chat", "datasets": ["tiiuae/falcon-refinedweb"], "eval_results": null, "language": ["en", "de", "es", "fr"], "library_name": null, "license": "unknown", "license_name": null, "license_link": null, "metrics": null, "model_name": "Falcon 180B Chat", "pipeline_tag": null, "tags": null, "... | <!-- 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 | [
"unknown"
] | [
"tiiuae/falcon-refinedweb"
] | [
"en",
"de",
"es",
"fr"
] | null | null | null | [
"AutoModelForCausalLM",
"falcon",
"FalconForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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6226b476e1cc4da22215575a | 634a9186a6003172 | 5f9f736c7dc6fbfa | 28,996 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 8 | michiyasunaga/LinkBERT-large | michiyasunaga | null | 3,000 | 168,792 | False | 2022-03-08T01:42:14Z | 2022-03-31T00:27:01Z | transformers | 14 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | d7bc175578ab3361bd13908e01f342e2dfbdba7c | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"exbert",
"linkbert",
"fill-mask",
"question-answering",
"text-classification",
"token-classification",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:2203.15827",
"license:apache-2.0",
"text-embeddings-inference",
"en... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["wikipedia", "bookcorpus"], "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": ["bert", "exbert", "linkbert", "feature-extraction", "fill-m... | ## LinkBERT-large
LinkBERT-large model pretrained on English Wikipedia articles along with hyperlink information. It is introduced in the paper [LinkBERT: Pretraining Language Models with Document Links (ACL 2022)](https://arxiv.org/abs/2203.15827). The code and data are available in [this repository](https://github... | null | [
"apache-2.0"
] | [
"wikipedia",
"bookcorpus"
] | [
"en"
] | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"question-answering",
"token-classification",
"feature-extraction",
"text-classification",
"fill-mask"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"text",
"logits",
"embeddings"
] |
65e7b13224312e85ac3f555e | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | state-spaces/mamba-1.4b-hf | state-spaces | null | 6,301 | 176,551 | False | 2024-03-05T23:56:34Z | 2024-03-06T00:44:32Z | transformers | 15 | 0 | null | text-generation | {"parameters": {"F32": 1372178432}, "total": 1372178432} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"tokenizer.json",
"tokenizer_config.json"
] | 6e46eae61c27280517feef46f536d16b91076f08 | [
"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|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": 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 | 1,372,178,432 | null | null | [
"AutoModelForCausalLM",
"mamba",
"MambaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64d623fc6db135cfc8a56473 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | numind/NuSentiment-multilingual | numind | null | 10 | 155,576 | False | 2023-08-11T12:05:16Z | 2024-01-26T10:52:59Z | transformers | 14 | 0 | null | feature-extraction | {"parameters": {"F32": 278043648}, "total": 278043648} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 0fbffb264466ab5aa62bd9c182493df3b0d1f794 | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"feature-extraction",
"sentiment-analysis",
"text-classification",
"generic",
"sentiment-classification",
"multilingual",
"en",
"ar",
"fr",
"de",
"pt",
"it",
"es",
"zh",
"ja",
"ko",
"license:mit",
"text-embeddings-inf... | null | {"architectures": ["XLMRobertaModel"], "model_type": "xlm-roberta", "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": null, "language": ["en", "ar", "fr", "de", "pt", "it", "es", "zh", "ja", "ko"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "feature-extraction", "tags": ["sentiment-analys... | ## Model
Base version of e5-multilingual finetunned on an annotated subset of mC4 (multilingual C4). This model provide generic embedding for sentiment analysis. Embeddings can be used out of the box or fine tune on specific datasets.
Blog post: https://www.numind.ai/blog/creating-task-specific-foundation-models-wit... | null | [
"mit"
] | null | [
"en",
"ar",
"fr",
"de",
"pt",
"it",
"es",
"zh",
"ja",
"ko"
] | 278,043,648 | null | null | [
"XLMRobertaModel",
"AutoModel",
"xlm-roberta"
] | [
"feature-extraction",
"text-classification"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc136468d709f17a5e4 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | deepset/bert-base-uncased-squad2 | deepset | null | 10,253 | 183,376 | False | 2022-03-02T23:29:05Z | 2024-09-24T15:52:14Z | transformers | 10 | 0 | [{"name": "deepset/bert-base-uncased-squad2", "results": [{"task": {"type": "question-answering", "name": "Question Answering"}, "dataset": {"name": "squad_v2", "type": "squad_v2", "config": "squad_v2", "split": "validation"}, "metrics": [{"type": "exact_match", "value": 75.6529, "name": "Exact Match", "verified": true... | question-answering | {"parameters": {"I64": 512, "F32": 108893186}, "total": 108893698} | [
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"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
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"vocab.txt"
] | de4f1b1d909d2017cb1496327a0668aedbd848e3 | [
"transformers",
"pytorch",
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"bert",
"question-answering",
"en",
"dataset:squad_v2",
"license:cc-by-4.0",
"model-index",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForQuestionAnswering"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"datasets": ["squad_v2"], "language": "en", "license": "cc-by-4.0", "model-index": [{"name": "deepset/bert-base-uncased-squad2", "results": [{"task": {"type": "question-answering", "name": "Question Answering"}, "dataset": {"name": "squad_v2", "type": "squad_v2", "config": "squad_v2", "split": "validation"}, "metrics"... | # bert-base-uncased for Extractive QA
## Overview
**Language model:** bert-base-uncased
**Language:** English
**Downstream-task:** Extractive QA
**Training data:** SQuAD 2.0
**Eval data:** SQuAD 2.0
**Code:** See [an example extractive QA pipeline built with Haystack](https://haystack.deepset.ai/tutorials/... | null | [
"cc-by-4.0"
] | [
"squad_v2"
] | [
"en"
] | 108,893,698 | null | null | [
"AutoModelForQuestionAnswering",
"bert",
"BertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6833fc5a579a13240f008607 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | optimum-internal-testing/tiny-random-qwen3_moe | optimum-internal-testing | null | 3,976 | 183,732 | False | 2025-05-26T05:30:02Z | 2025-05-26T05:37:37Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"F32": 9970624}, "total": 9970624} | [
".gitattributes",
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"added_tokens.json",
"chat_template.jinja",
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"generation_config.json",
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"conversational",
"arxiv:1910.09700",
"endpoints_compatible",
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] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": 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 | 9,970,624 | null | null | [
"qwen3_moe",
"AutoModelForCausalLM",
"Qwen3MoeForCausalLM"
] | [
"text-generation"
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"text"
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65148276ac849a6655d267e9 | 5385e084548307e9 | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
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"Replace",
"ByteFallback",
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] | 156 | TheBloke/Mistral-7B-v0.1-AWQ | TheBloke | {
"models": [
{
"_id": "650aedb6238a644cb93a52c3",
"id": "mistralai/Mistral-7B-v0.1"
}
],
"relation": "quantized"
} | 683 | 161,709 | False | 2023-09-27T19:28:54Z | 2023-11-09T18:17:59Z | transformers | 33 | 0 | null | text-generation | {"parameters": {"I32": 6979321856, "BF16": 262410240}, "total": 7241732096} | [
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<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<d... | null | [
"apache-2.0"
] | null | null | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
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65721446d0ae612d410ace45 | 6949732424a8d297 | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 42 | LLM360/Amber | LLM360 | null | 81,581 | 247,344 | False | 2023-12-07T18:51:50Z | 2025-10-10T21:53:21Z | transformers | 72 | 0 | null | text-generation | {"parameters": {"BF16": 6738415616}, "total": 6738415616} | [
".gitattributes",
"README.md",
"amber-arc-curve.pdf",
"amber-arc-curve.png",
"amber-hellaswag-curve.pdf",
"amber-hellaswag-curve.png",
"amber-mmlu-curve.pdf",
"amber-mmlu-curve.png",
"amber-truthfulqa-curve.pdf",
"amber-truthfulqa-curve.png",
"amber_logo.png",
"arc.png",
"config.json",
"ev... | 2d35937a32b99aec0d59dd772b54e1bb08719a7f | [
"transformers",
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"llama",
"text-generation",
"nlp",
"llm",
"en",
"arxiv:2312.06550",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": 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": ["nlp", "llm"]} | # Amber
<center><img src="amber_logo.png" alt="amber logo" width="150"/></center>
Amber is an7B English language model with the LLaMA architecture. Amber is part of LLM360's Pebble model series.
360 model checkpoints and the full data sequence are available under the Apache 2.0 license.
## Evaluations
| Metric ... | null | [
"apache-2.0"
] | null | [
"en"
] | 6,738,415,616 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65ae969e69cd2991ef185307 | fa3eb8b5ab2b6741 | 0bb73d739c8c3372 | 31,102 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 753 | DeepMount00/Italian_NER_XXL | DeepMount00 | null | 15,638 | 191,635 | False | 2024-01-22T16:23:58Z | 2025-06-11T10:04:35Z | transformers | 50 | 0 | [{"name": "Italin_NER_XXL", "results": []}] | token-classification | {"parameters": {"F32": 110195061}, "total": 110195061} | [
".gitattributes",
"README.md",
"config.json",
"gitattributes",
"id2tag.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 2ec7bb9bf7c23b62141e31a74ab4ccb11dd0bd82 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"legal",
"finance",
"privacy",
"it",
"license:apache-2.0",
"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": [], "language": ["it"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "Italin_NER_XXL", "pipeline_tag": null, "tags": ["legal", "finance", "privacy"], "widget": [{"text": "Mario Rossi, nato... | # Italian_NER_XXL
---
**💡 Found this resource helpful?** Creating and maintaining open source AI models and datasets requires significant computational resources. If this work has been valuable to you, consider [supporting my research](https://buymeacoffee.com/michele.montebovi) to help me continue building tools th... | null | [
"apache-2.0"
] | null | [
"it"
] | 110,195,061 | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6647f2db88f930340c68c125 | c804cc507104218c | cad4902422b140fb | 64,000 | BPE | 110,029 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 806 | qnguyen3/Master-Yi-9B | qnguyen3 | null | 7,847 | 192,665 | False | 2024-05-18T00:14:19Z | 2024-05-20T11:21:22Z | transformers | 17 | 0 | null | text-generation | {"parameters": {"BF16": 8829407232}, "total": 8829407232} | [
".gitattributes",
"Master-Yi-9B.webp",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
"model.safetensors.inde... | e30c2b86d68053dd99bb2159f6ff04636786ac32 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|startoftext|>", "chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|im_start|>system\\n' + system_message + '<|im_... | {
"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} | ## Model Description
Master is a collection of LLMs trained using human-collected seed questions and regenerate the answers with a mixture of high performance Open-source LLMs.
**Master-Yi-9B** is trained using the ORPO technique. The model shows strong abilities in reasoning on coding and math questions.
**Quantize... | null | [
"apache-2.0"
] | null | null | 8,829,407,232 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68830f190d96f185cd243ef5 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | Qwen/Qwen3-235B-A22B-Thinking-2507 | Qwen | null | 76,171 | 430,332 | False | 2025-07-25T04:59:05Z | 2025-08-17T08:20:17Z | transformers | 402 | 1 | null | text-generation | null | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"config_1m.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00118.safetensors",
"model-00002-of-00118.safetensors",
"model-00003-of-00118.safetensors",
"model-00004-of-00118.safetensors",
"model-00005-of-00118.safetensors",... | 6cbffae6d8e28b986a6b17bd36f42f9fa0f1f0a5 | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"conversational",
"arxiv:2402.17463",
"arxiv:2407.02490",
"arxiv:2501.15383",
"arxiv:2404.06654",
"arxiv:2505.09388",
"license:apache-2.0",
"eval-results",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generati... | # Qwen3-235B-A22B-Thinking-2507
<a href="https://chat.qwen.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Highlights
Over the past three months, we have con... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507/blob/main/LICENSE"
] | null | null | null | null | null | [
"qwen3_moe",
"AutoModelForCausalLM",
"Qwen3MoeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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