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## Introduction
Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. In comparison with the previous released Qwen, the improvements include:
* 8 model sizes, including 0.5B, 1.8B, 4B, 7B, 14B, 32B and 72B dense models, and an MoE ... | null | [
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"en"
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} | 15,461 | 747,729 | False | 2025-02-15T10:54:57Z | 2025-02-15T23:02:19Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F32": 475344, "BF16": 1227100160, "U8": 7015836218}, "total": 8243411722} | [
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<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/llama-31-collection-6753dca76f47d9ce1696495f">our collection</a> for versions of Llama 3.1 including 4-bit + 16b-bit formats.</strong>
</p>
<div style="display: flex; gap: 5px; align-items: cente... | null | [
"llama3.1"
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"text"
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<a href="https://chat.qwen.ai/?model=Qwen3-30B-A3B-2507" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Highlights
We introduce... | null | [
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This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base) on [Djacon/ru_goemotions](https://huggingface.co/datasets/Djacon/ru_goemotions).
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An Apache-2 licensed chatbot trained over a massive curated corpus of assistant interactions including word problems, multi-turn dialogue, code, poems, songs, and stories.
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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"... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Meta-Llama-3.2-3B", "datasets": null, "eval_results": [], "language": ["en"], "library_name": "transformers", "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": "Hermes-3-Llama-3.2-3B", "pipeline_tag": null, "tags": ["Llama-3", "instruct", "finetun... | # Hermes 3 - Llama-3.2 3B
## Model Description
Hermes 3 3B is a small but mighty new addition to the Hermes series of LLMs by Nous Research, and is Nous's first fine-tune in this parameter class.... | null | [
"llama3"
] | null | [
"en"
] | 3,212,749,824 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
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"text"
] | [
"text"
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68780aece2a2463f01c43547 | 649749f22f7229cd | 66be3297e0980489 | 28,895 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 383 | OpenMed/OpenMed-NER-PathologyDetect-PubMed-v2-109M | OpenMed | null | 113,996 | 1,212,928 | False | 2025-07-16T20:26:20Z | 2025-08-05T09:39:51Z | transformers | 5 | 0 | null | token-classification | {"parameters": {"BF16": 108893955}, "total": 108893955} | [
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"tokenizer_config.json",
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"apache-2.0"
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6888aae7c54baad7997d7b4b | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | Qwen/Qwen3-30B-A3B-Thinking-2507 | Qwen | null | 1,068,226 | 3,208,511 | False | 2025-07-29T11:05:11Z | 2025-08-17T08:20:51Z | transformers | 371 | 1 | null | text-generation | {"parameters": {"BF16": 30532122624}, "total": 30532122624} | [
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<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 conti... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507/blob/main/LICENSE"
] | null | null | 30,532,122,624 | null | null | [
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"text"
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63e793cd3b872cfb1766d7af | e2dc92900d8a1be7 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 462 | MoritzLaurer/multilingual-MiniLMv2-L6-mnli-xnli | MoritzLaurer | null | 11,460 | 599,511 | False | 2023-02-11T13:10:37Z | 2024-04-22T11:03:52Z | transformers | 47 | 0 | null | zero-shot-classification | {"parameters": {"I64": 514, "F32": 106995075}, "total": 106995589} | [
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... | 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": "... | {
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"pipeline_tag": "text-classification",
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} | {"base_model": null, "datasets": ["multi_nli", "xnli"], "eval_results": null, "language": ["multilingual", "en", "ar", "bg", "de", "el", "es", "fr", "hi", "ru", "sw", "th", "tr", "ur", "vi", "zh"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name":... | ---
# Multilingual MiniLMv2-L6-mnli-xnli
## Model description
This multilingual model can perform natural language inference (NLI) on 100+ languages and is therefore also
suitable for multilingual zero-shot classification. The underlying multilingual-MiniLM-L6 model was created
by Microsoft and was distilled from XLM... | null | [
"mit"
] | [
"multi_nli",
"xnli"
] | [
"multilingual",
"en",
"ar",
"bg",
"de",
"el",
"es",
"fr",
"hi",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh"
] | 106,995,589 | null | [
"accuracy"
] | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"zero-shot-classification",
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64821504707a292dcb1cea79 | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | facebook/musicgen-large | facebook | null | 19,778 | 627,284 | False | 2023-06-08T17:51:00Z | 2023-11-17T15:25:38Z | transformers | 525 | 1 | null | text-to-audio | null | [
".gitattributes",
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"musicgen",
"text-to-audio",
"arxiv:2306.05284",
"license:cc-by-nc-4.0",
"endpoints_compatible",
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] | null | {"architectures": ["MusicgenForConditionalGeneration"], "model_type": "musicgen", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTextToWaveform",
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"pipeline_tag": "text-to-audio",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["musicgen"], "inference": true} | # MusicGen - Large - 3.3B
MusicGen is a text-to-music model capable of genreating high-quality music samples conditioned on text descriptions or audio prompts.
It is a single stage auto-regressive Transformer model trained over a 32kHz EnCodec tokenizer with 4 codebooks sampled at 50 Hz.
Unlike existing methods, like... | null | [
"cc-by-nc-4.0"
] | null | null | null | null | null | [
"musicgen",
"MusicgenForConditionalGeneration",
"AutoModelForTextToWaveform"
] | [
"text-to-audio"
] | [
"text"
] | [
"text"
] | [
"audio"
] |
662304b43c85352399cb4b8c | 39b1e434a495263c | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 349 | VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct | VAGOsolutions | null | 13,506 | 633,161 | False | 2024-04-19T23:56:36Z | 2024-04-29T18:28:16Z | transformers | 56 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
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"model.safetensors.index.json",
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"... | 37127c44d7c0fb56cef817270c4b1a6802d8793a | [
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["de", "en"], "library_name": null, "license": "other", "license_name": "llama3", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["two stage dpo", "dpo"], "extra_gated_prompt": "### META LLAMA 3 COMMU... | 
## VAGO solutions Llama-3-SauerkrautLM-8b-Instruct
Introducing **Llama-3-SauerkrautLM-8b-Instruct** – our Sauerkraut version of the powerful [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.c... | null | [
"other",
"llama3",
"LICENSE"
] | null | [
"de",
"en"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
623c96f932d31e74e36e7925 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | optimum/distilbert-base-uncased-finetuned-sst-2-english | optimum | null | 2,028 | 570,471 | False | 2022-03-24T16:06:17Z | 2022-06-13T13:43:16Z | transformers | 2 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"model.onnx",
"special_tokens_map.json",
"tokenizer.json",
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"vocab.txt"
] | 4fddcd234d65e78d9de14e8ac55c32035bf9f1ee | [
"transformers",
"onnx",
"text-classification",
"en",
"dataset:sst2",
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] | null | {"architectures": ["DistilBertForSequenceClassification"], "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
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} | {"base_model": null, "datasets": ["sst2"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ONNX convert DistilBERT base uncased finetuned SST-2
## Conversion of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english)
This model is a fine-tune checkpoint of [DistilBERT-base-uncased](https://huggingface.co/distilbert-base-uncased), fine-tune... | null | [
"apache-2.0"
] | [
"sst2"
] | [
"en"
] | null | null | null | [
"DistilBertForSequenceClassification",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
64ec5b3cde393e513c7e0a04 | 8e1b96de70a6f0c8 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 463 | MarcoMancini/low-law-emb | MarcoMancini | null | 1,553 | 574,131 | False | 2023-08-28T08:30:52Z | 2023-09-28T09:55:02Z | transformers | 0 | 0 | null | null | null | [
".gitattributes",
"1_Pooling/config.json",
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"pytorch_model.bin",
"sentence_bert_config.json",
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] | 3bf5d3f2a22029d974115fa3036954424803362a | [
"transformers",
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null
] | null | null | null |
636197c46bd72c97d0037877 | c97a6495c5454551 | f26f356cd728caa8 | 49,408 | BPE | 48,894 | true | true | true | true | 2 | Sequence | Sequence | ByteLevel | [
"NFC",
"Replace",
"Lowercase"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 2 | timm/vit_large_patch14_clip_224.openai | timm | null | 16,316 | 596,441 | False | 2022-11-01T22:03:48Z | 2025-01-21T21:59:25Z | timm | 2 | 0 | null | null | null | [
".gitattributes",
"README.md",
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"open_clip_model.safetensors",
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"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 18d0535469bb561bf468d76c1d73aa35156c922b | [
"timm",
"pytorch",
"open_clip",
"safetensors",
"vision",
"transformers",
"arxiv:2103.00020",
"arxiv:1908.04913",
"license:apache-2.0",
"region:us"
] | null | {"tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "timm", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["timm", "vision", "transformers"]} | # CLIP (OpenAI model for timm)
## Model Details
The CLIP model was developed by researchers at OpenAI to learn about what contributes to robustness in computer vision tasks. The model was also developed to test the ability of models to generalize to arbitrary image classification tasks in a zero-shot manner. It was no... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModel"
] | [
null
] | null | null | null |
664a2e88006242829e49989a | 38805d8eca7d7c72 | af1fea6666013553 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 354 | openbmb/MiniCPM-Llama3-V-2_5-int4 | openbmb | {
"models": [
{
"_id": "6649c024e74442492218cf6a",
"id": "openbmb/MiniCPM-Llama3-V-2_5"
}
],
"relation": "quantized"
} | 728 | 565,772 | False | 2024-05-19T16:53:28Z | 2025-02-27T08:25:38Z | transformers | 79 | 1 | null | visual-question-answering | {"parameters": {"F32": 546555, "F16": 1182531824, "U8": 7584513612}, "total": 8767591991} | [
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"to... | e4f09e1a60c2a7e2861dea6af90d061fec96f6ae | [
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"base_model:quantized:openbmb/MiniCPM-Llama3-V-2_5",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["MiniCPMV"], "auto_map": {"AutoConfig": "configuration_minicpm.MiniCPMVConfig", "AutoModel": "modeling_minicpmv.MiniCPMV", "AutoModelForCausalLM": "modeling_minicpmv.MiniCPMV"}, "model_type": "minicpmv", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbyte... | {
"auto_model": "AutoModel",
"custom_class": "modeling_minicpmv.MiniCPMV",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["openbmb/MiniCPM-Llama3-V-2_5"], "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": "visual-question-answering", "tags": null} | ## MiniCPM-Llama3-V 2.5 int4
This is the int4 quantized version of [MiniCPM-Llama3-V 2.5](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5).
Running with int4 version would use lower GPU memory (about 9GB).
## Usage
Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.10：
```... | null | null | null | null | 8,767,591,991 | null | null | [
"AutoModel",
"MiniCPMV",
"minicpmv",
"modeling_minicpmv.MiniCPMV"
] | [
"feature-extraction",
"visual-question-answering"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"logits",
"embeddings"
] |
687523b49ee7caed125d5dc1 | 52f24e37c2a463b7 | e228821354aa0ea9 | 64,400 | BPE | 63,683 | false | true | true | true | 507 | null | Sequence | Sequence | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 404 | lmstudio-community/LFM2-1.2B-MLX-8bit | lmstudio-community | {
"models": [
{
"_id": "686fabae2fb74b6dbfe2dc8b",
"id": "LiquidAI/LFM2-1.2B"
}
],
"relation": "quantized"
} | 23,440 | 697,729 | False | 2025-07-14T15:35:16Z | 2025-07-22T16:36:16Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"BF16": 36698880, "U32": 292552704}, "total": 329251584} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | c66e73e60e2069ca5ddb251415bf04c8c3226f63 | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"liquid",
"edge",
"mlx",
"conversational",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"base_model:LiquidAI/LFM2-1.2B",
"base_model:quantized:LiquidAI/LFM2-1.2B",
"license:other",
"endpoints_compatible",
"8-bit",
... | null | {"architectures": ["Lfm2ForCausalLM"], "model_type": "lfm2", "quantization_config": {"bits": 8}, "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|im_end|>", "pad_token": "<|pad|>", "use_default_system_prompt": false, "chat_template": "{{bos_token}}{% for message in messages %}{{'<|im_start|>' + mess... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "LiquidAI/LFM2-1.2B", "datasets": null, "eval_results": null, "language": ["en", "ar", "zh", "fr", "de", "ja", "ko", "es"], "library_name": "transformers", "license": "other", "license_name": "lfm1.0", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tag... | null | null | [
"other",
"lfm1.0",
"LICENSE"
] | null | [
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es"
] | 329,251,584 | null | null | [
"Lfm2ForCausalLM",
"AutoModelForCausalLM",
"lfm2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1802d0 | 120c2ce442fd8f55 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 17 | sentence-transformers/multi-qa-MiniLM-L6-dot-v1 | sentence-transformers | null | 99,277 | 1,031,541 | False | 2022-03-02T23:29:05Z | 2024-11-05T20:22:38Z | sentence-transformers | 17 | 0 | null | sentence-similarity | {"parameters": {"I64": 512, "F32": 22713216}, "total": 22713728} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"data_config.json",
"model.safetensors",
"modules.json",
"onnx/model.onnx",
"onnx/model_O1.onnx",
"onnx/model_O2.onnx",
"onnx/model_O3.onnx",
"onnx/model_O4.onnx",
"onnx/model_qint8_... | 4151c507ffb0f2fcd311cf431f54b5fc7d097851 | [
"sentence-transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"openvino",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"en",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "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", "sent... | # multi-qa-MiniLM-L6-dot-v1
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and was designed for **semantic search**. It has been trained on 215M (question, answer) pairs from diverse sources. For an introduction to semantic search, ... | null | null | null | [
"en"
] | 22,713,728 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
63dd6761ad14107542d5583c | 58ea2d1bf19bbd5b | 70cc02c676d4693d | 901,629 | Unigram | null | true | true | true | true | 5 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 464 | facebook/xlm-v-base | facebook | null | 3,517 | 588,369 | False | 2023-02-03T19:58:25Z | 2023-02-08T08:15:57Z | transformers | 39 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"tokenizer.json"
] | 68c75dd7733d2640b3a98114e3e94196dc543fe1 | [
"transformers",
"pytorch",
"xlm-roberta",
"fill-mask",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha... | null | {"architectures": ["XLMRobertaForMaskedLM"], "model_type": "xlm-roberta"} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["multilingual", "af", "am", "ar", "as", "az", "be", "bg", "bn", "br", "bs", "ca", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "he", "hi", "hr", "hu", "hy", "id", "is", "it", "j... | # XLM-V (Base-sized model)
XLM-V is multilingual language model with a one million token vocabulary trained on 2.5TB of data from Common Crawl (same as XLM-R).
It was introduced in the [XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models](https://arxiv.org/abs/2301.10472)
paper by Davis ... | null | [
"mit"
] | null | [
"multilingual",
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"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
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"fi",
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"gl",
"gu",
"ha",
"he",
"hi",
"hr",
"hu",
"hy",
"id",
"is",
"i... | null | null | null | [
"AutoModelForMaskedLM",
"xlm-roberta",
"XLMRobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
632560aa78ba0c1d7958e4e8 | 634a9186a6003172 | 5f9f736c7dc6fbfa | 28,996 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 8 | Charangan/MedBERT | Charangan | null | 1,834 | 565,206 | False | 2022-09-17T05:52:42Z | 2023-01-13T11:53:33Z | transformers | 18 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 315cdfc82d4d6eb1cabfb35444095e5b975d4d9d | [
"transformers",
"pytorch",
"bert",
"pretraining",
"fill-mask",
"en",
"arxiv:1904.03323",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForPreTraining"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForPreTraining",
"custom_class": null,
"pipeline_tag": "pretraining",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["fill-mask"]} | # MedBERT Model
**MedBERT** is a newly pre-trained transformer-based language model for biomedical named entity recognition: initialized with [Bio_ClinicalBERT](https://arxiv.org/abs/1904.03323) & pre-trained on N2C2, BioNLP, and CRAFT community datasets.
## Pretraining
### Data
The `MedBERT` model was trained on N2... | null | [
"mit"
] | null | [
"en"
] | null | null | null | [
"bert",
"AutoModelForPreTraining",
"BertForPreTraining"
] | [
"fill-mask",
"pretraining"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
631246575beb528b5c10b073 | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | KoboldAI/GPT-NeoX-20B-Erebus | KoboldAI | null | 1,231 | 564,601 | False | 2022-09-02T18:07:19Z | 2022-09-26T19:05:19Z | transformers | 86 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model-00001-of-00023.bin",
"pytorch_model-00002-of-00023.bin",
"pytorch_model-00003-of-00023.bin",
"pytorch_model-00004-of-00023.bin",
"pytorch_model-00005-of-00023.bin",
"pytorch_model-00006-of-00023.bin",
"pytorch_model-00007... | 1a80940a290452af71caf17a8e520955eb338e0f | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"en",
"arxiv:2204.06745",
"license:apache-2.0",
"text-generation-inference",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "inference": false} | # GPT-NeoX-20B-Erebus
## Model description
This is the second generation of the original Shinen made by Mr. Seeker. The full dataset consists of 6 different sources, all surrounding the "Adult" theme. The name "Erebus" comes from the greek mythology, also named "darkness". This is in line with Shin'en, or "deep abyss".... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 358 | zai-org/GLM-4-32B-0414 | zai-org | null | 1,724 | 657,615 | False | 2025-04-07T12:53:41Z | 2025-05-01T15:42:37Z | transformers | 483 | 0 | null | text-generation | null | [
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"model-00001-of-00014.safetensors",
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"model-00003-of-00014.safetensors",
"model-00004-of-00014.safetensors",
"model-00005-of-00014.safetensors",
"model-0... | 077b5c2f5c43bd3239fd605a0600229e8facbd4a | [
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"glm4",
"text-generation",
"conversational",
"zh",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Glm4ForCausalLM"], "model_type": "glm4", "tokenizer_config": {"chat_template": "[gMASK]<sop>{%- if tools -%}<|system|>\n# \u53ef\u7528\u5de5\u5177\n{% for tool in tools %}{%- set function = tool.function if tool.get(\"function\") else tool %}\n\n## {{ function.name }}\n\n{{ function | tojson(indent=... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh", "en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | null | null | [
"mit"
] | null | [
"zh",
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"glm4",
"Glm4ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63c80f57a0c5c8cfa84b44a2 | a291a5b7b160e3e0 | 2b950a81ab105286 | 1,000 | BPE | 806 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 465 | fxmarty/tiny-testing-gpt2-remote-code | fxmarty | null | 1,066 | 560,545 | False | 2023-01-18T15:25:11Z | 2023-01-18T15:41:38Z | transformers | 1 | 0 | null | text-generation | null | [
".gitattributes",
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"__init__.py",
"config.json",
"create_model.py",
"merges.txt",
"modeling_gpt2.py",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 79b7db0a801ca1f783cd3c2f913d18611701399b | [
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"gpt2",
"text-generation",
"custom_code",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2CustomLMHeadModel"], "auto_map": {"AutoModelForCausalLM": "modeling_gpt2.GPT2CustomLMHeadModel"}, "model_type": "gpt2", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_gpt2.GPT2CustomLMHeadModel",
"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} | null | null | [
"apache-2.0"
] | null | null | null | null | null | [
"gpt2",
"GPT2CustomLMHeadModel",
"AutoModelForCausalLM",
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"text-generation"
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"text"
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671e95bbb91f5a4a2436a3c4 | 5b8a6156b5b6e013 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 37 | cybersectony/phishing-email-detection-distilbert_v2.4.1 | cybersectony | {
"models": [
{
"_id": "621ffdc036468d709f174347",
"id": "distilbert/distilbert-base-uncased"
}
],
"relation": "finetune"
} | 294,687 | 1,938,711 | False | 2024-10-27T19:34:19Z | 2024-10-28T10:02:55Z | transformers | 24 | 0 | null | text-classification | {"parameters": {"F32": 66956548}, "total": 66956548} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6724dec17360ab1f6450553f1d950404f66a5dde | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"en",
"dataset:cybersectony/PhishingEmailDetectionv2.0",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_co... | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "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": ["distilbert/distilbert-base-uncased"], "datasets": ["cybersectony/PhishingEmailDetectionv2.0"], "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"... | # A distilBERT based Phishing Email Detection Model
## Model Overview
This model is based on DistilBERT and has been fine-tuned for multilabel classification of Emails and URLs as safe or potentially phishing.
## Key Specifications
- __Base Architecture:__ DistilBERT
- __Task:__ Multilabel Classification
- __Fine-tun... | null | [
"apache-2.0"
] | [
"cybersectony/PhishingEmailDetectionv2.0"
] | [
"en"
] | 66,956,548 | null | null | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
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"NFC"
] | [
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"ByteLevel"
] | 466 | Tiiny/SmallThinker-3B-Preview | Tiiny | {
"models": [
{
"_id": "66e98d74d4219fc3f1db215f",
"id": "Qwen/Qwen2.5-3B-Instruct"
}
],
"relation": "finetune"
} | 1,183 | 613,739 | False | 2024-12-12T11:56:09Z | 2025-01-16T10:36:10Z | transformers | 416 | 0 | null | text-generation | {"parameters": {"BF16": 3397103616}, "total": 3397103616} | [
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"result/aime24_eval.json",
"resu... | 2ca6a4093f3e9f178d61a5364a0335877a4e9b07 | [
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"conversational",
"en",
"dataset:PowerInfer/QWQ-LONGCOT-500K",
"dataset:PowerInfer/LONGCOT-Refine-500K",
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## What does the model do?
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<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/deplot_architecture.png"
alt="drawing" width="600"/>
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Using the model](#using-the-model)
2. [Contribution](#contribution)
3. [Citation](#c... | null | [
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<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
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## Model summary
This model can be used for **semantic search** and **documents retrieval** to find relevant passages based on a query.
It was trained on a machine translated **MSMARCO dataset** for _german_ with **hard negatives** and **Margin MSE loss**.
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Model is fine-tuned on distilroberta-base model from the huggingface repository.
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"arxiv:2503.22673",... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Salesforce/APIGen-MT-5k", "Salesforce/xlam-function-calling-60k"], "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", "... | null | null | [
"cc-by-nc-4.0"
] | [
"Salesforce/APIGen-MT-5k",
"Salesforce/xlam-function-calling-60k"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67009f18dfea4662452cd07a | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | mlx-community/Meta-Llama-3.1-70B-Instruct-bf16-CORRECTED | mlx-community | {
"models": [
{
"_id": "66969ad27a033bf62173f3e2",
"id": "meta-llama/Llama-3.1-70B-Instruct"
}
],
"relation": "finetune"
} | 302 | 546,915 | False | 2024-10-05T02:06:16Z | 2024-10-05T04:34:44Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
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"model-00002-of-00028.safetensors",
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... | 65f2270fdd80ed4cca1409a9048bb2824e203c22 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"mlx",
"conversational",
"en",
"de",
"fr",
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"th",
"base_model:meta-llama/Llama-3.1-70B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-70B-Instruct",... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Llama-3.1-70B-Instruct", "datasets": null, "eval_results": null, "language": ["en", "de", "fr", "it", "pt", "hi", "es", "th"], "library_name": "transformers", "license": "llama3.1", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generati... | # vanakema/Meta-Llama-3.1-70B-bf16-forcebf16
The Model [vanakema/Meta-Llama-3.1-70B-bf16-forcebf16](https://huggingface.co/vanakema/Meta-Llama-3.1-70B-bf16-forcebf16) was converted to MLX format from [meta-llama/Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct) using mlx-lm version **0.... | null | [
"llama3.1"
] | null | [
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68936876b9987f61d4207441 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | lmstudio-community/Qwen3-4B-Instruct-2507-MLX-4bit | lmstudio-community | {
"models": [
{
"_id": "6891e3bb084ce75acffb033d",
"id": "Qwen/Qwen3-4B-Instruct-2507"
}
],
"relation": "quantized"
} | 63,124 | 824,250 | False | 2025-08-06T14:36:38Z | 2025-08-06T14:37:05Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"BF16": 125892096, "U32": 502784000}, "total": 628676096} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
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"merges.txt",
"model.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 7479749d4b89a9c12057d32a0e5ed07b2829e721 | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"mlx",
"conversational",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:quantized:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"region:us"
] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "quantization_config": {"bits": 4}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'sy... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-4B-Instruct-2507", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_ta... | ## 💫 Community Model> Qwen3-4B-Instruct-2507 by Qwen
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [Qwen](https://huggingface.co/Qwen)<br>
**Origin... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE"
] | null | null | 628,676,096 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
672f5934437aab8fbf29192b | 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-Instruct-GPTQ-Int4 | Qwen | {
"models": [
{
"_id": "672b1f9e956e6880fdb8c1e5",
"id": "Qwen/Qwen2.5-Coder-32B-Instruct"
}
],
"relation": "quantized"
} | 14,542 | 639,870 | False | 2024-11-09T12:44:36Z | 2024-11-18T12:55:09Z | transformers | 24 | 0 | null | text-generation | {"parameters": {"I32": 31205621760, "F16": 1558254592}, "total": 32763876352} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
"model.safetensor... | 5fece1e232475f4da75cf0e4283606a3186fee8a | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"code",
"codeqwen",
"chat",
"qwen",
"qwen-coder",
"conversational",
"en",
"arxiv:2409.12186",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-Coder-32B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-Coder-32B-In... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen2.5-Coder-32B-Instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, ... | # Qwen2.5-Coder-32B-Instruct-GPTQ-Int4
## 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. Qwe... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct/blob/main/LICENSE"
] | null | [
"en"
] | 32,763,876,352 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
670d5070d6ac639441760efc | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | Skywork/Skywork-Reward-Llama-3.1-8B-v0.2 | Skywork | {
"models": [
{
"_id": "6698d8a0653e4babe21e1e7d",
"id": "meta-llama/Llama-3.1-8B-Instruct"
}
],
"relation": "finetune"
} | 52,491 | 677,892 | False | 2024-10-14T17:10:08Z | 2024-10-25T01:22:28Z | transformers | 41 | 2 | null | text-classification | {"parameters": {"BF16": 7504928768}, "total": 7504928768} | [
".gitattributes",
"README.md",
"config.json",
"misc/Skywork Community License.pdf",
"misc/Skywork 模型社区许可协议.pdf",
"misc/fig.jpg",
"model-00001-of-00004.safetensors",
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"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.inde... | d4117fbfd81b72f41b96341238baa1e3e90a4ce1 | [
"transformers",
"safetensors",
"llama",
"text-classification",
"dataset:Skywork/Skywork-Reward-Preference-80K-v0.2",
"arxiv:2410.18451",
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"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"text-embeddings-inference",
"endpoints_compatible",
"de... | null | {"architectures": ["LlamaForSequenceClassification"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Llama-3.1-8B-Instruct", "datasets": ["Skywork/Skywork-Reward-Preference-80K-v0.2"], "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", ... | <div align="center">
<img src="misc/fig.jpg" width="400"/>
🤗 <a href="https://huggingface.co/Skywork" target="_blank">Hugging Face</a> • 🤖 <a href="https://modelscope.cn/organization/Skywork" target="_blank">ModelScope</a>
<br>
<br>
<br>
</div>
# Skywork Reward Model Series
> IMPORTANT:
> This model was trained usi... | null | null | [
"Skywork/Skywork-Reward-Preference-80K-v0.2"
] | null | 7,504,928,768 | null | null | [
"LlamaForSequenceClassification",
"llama",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6575e7258b44ef012b71c325 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | Deci/DeciLM-7B-instruct | Deci | null | 4,372 | 556,125 | False | 2023-12-10T16:28:21Z | 2024-02-21T16:05:34Z | transformers | 95 | 0 | null | text-generation | {"parameters": {"BF16": 7043551232}, "total": 7043551232} | [
".gitattributes",
"README.md",
"benchmark_hf_model.py",
"config.json",
"configuration_decilm.py",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"modeling_decilm.py",
"special_tokens_map.json",
"tokeni... | 4adc7aa9efe61b47b0a98b2cc94527d9c45c3b4f | [
"transformers",
"safetensors",
"deci",
"text-generation",
"conversational",
"custom_code",
"en",
"dataset:Open-Orca/SlimOrca",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["DeciLMForCausalLM"], "auto_map": {"AutoConfig": "configuration_decilm.DeciLMConfig", "AutoModelForCausalLM": "modeling_decilm.DeciLMForCausalLM"}, "model_type": "deci", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_decilm.DeciLMForCausalLM",
"pipeline_tag": "text-generation",
"processor": null
} | {"base_model": null, "datasets": ["Open-Orca/SlimOrca"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # DeciLM-7B-instruct
DeciLM-7B-instruct is a model for short-form instruction following. It is built by LoRA fine-tuning on the [SlimOrca dataset](https://huggingface.co/datasets/Open-Orca/SlimOrca).
## Model Details
### Model Description
DeciLM-7B-instruct is a derivative of the recently released [DeciLM-7B](http... | null | [
"apache-2.0"
] | [
"Open-Orca/SlimOrca"
] | [
"en"
] | 7,043,551,232 | null | null | [
"DeciLMForCausalLM",
"AutoModelForCausalLM",
"modeling_decilm.DeciLMForCausalLM",
"deci"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
653f4646c2307cc448a98395 | bc2c6b1ccadaf507 | d1e0dcc971dc8303 | 32,002 | BPE | 58,980 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 329 | openchat/openchat_3.5 | openchat | null | 2,696 | 563,041 | False | 2023-10-30T05:59:34Z | 2024-05-18T18:09:11Z | transformers | 1,140 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"openchat.json",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_con... | 0fc98e324280bc4bf5d2c30ecf7b97b84fb8a19b | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"openchat",
"C-RLFT",
"conversational",
"dataset:openchat/openchat_sharegpt4_dataset",
"dataset:imone/OpenOrca_FLAN",
"dataset:LDJnr/LessWrong-Amplify-Instruct",
"dataset:LDJnr/Pure-Dove",
"dataset:LDJnr/Verified-Camel",
"dataset:tiedo... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{ bos_token }}{% for message in messages %}{{ 'GPT4 Correct ' + message['role'].title() + ': ' + message['content'] + '<|end_of_turn|>'}}{% endfor %}{% if add_generation_prompt %}{{ 'GPT4 Corre... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["openchat/openchat_sharegpt4_dataset", "imone/OpenOrca_FLAN", "LDJnr/LessWrong-Amplify-Instruct", "LDJnr/Pure-Dove", "LDJnr/Verified-Camel", "tiedong/goat", "glaiveai/glaive-code-assistant", "meta-math/MetaMathQA", "OpenAssistant/oasst_top1_2023-08-25", "TIGER-Lab/MathInstruct"], "eval... | # OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
<div align="center">
<img src="https://raw.githubusercontent.com/imoneoi/openchat/master/assets/logo_new.png" style="width: 65%">
</div>
<p align="center">
<a href="https://github.com/imoneoi/openchat">GitHub Repo</a> •
<a href="https://o... | null | [
"apache-2.0"
] | [
"openchat/openchat_sharegpt4_dataset",
"imone/OpenOrca_FLAN",
"LDJnr/LessWrong-Amplify-Instruct",
"LDJnr/Pure-Dove",
"LDJnr/Verified-Camel",
"tiedong/goat",
"glaiveai/glaive-code-assistant",
"meta-math/MetaMathQA",
"OpenAssistant/oasst_top1_2023-08-25",
"TIGER-Lab/MathInstruct"
] | null | null | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64d0f2a0c0c627dfa7ff7272 | 2226806e84342173 | c52274a217b96db0 | 37,788 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 470 | readerbench/ro-sentiment | readerbench | {
"models": [
{
"_id": "621ffdc136468d709f17f359",
"id": "readerbench/RoBERT-base"
}
],
"relation": "finetune"
} | 69 | 553,547 | False | 2023-08-07T13:33:20Z | 2023-08-08T10:31:58Z | transformers | 1 | 0 | [{"name": "ro-sentiment", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"type": "ro_sent", "name": "Rommanian Sentiment Dataset", "config": "default", "split": "all"}, "metrics": [{"type": "accuracy", "value": 0.85, "name": "Accuracy", "verified": false}, {"type": "pre... | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | b438507c39ad395df62a6c52a5bd51806bc08fd6 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"sentiment",
"classification",
"romanian",
"nlp",
"ro",
"dataset:decathlon_reviews",
"dataset:cinemagia_reviews",
"base_model:readerbench/RoBERT-base",
"base_model:finetune:readerbench/RoBERT-base",
"model-index",
"text-embeddings... | 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": "readerbench/RoBERT-base", "datasets": ["decathlon_reviews", "cinemagia_reviews"], "language": ["ro"], "metrics": ["accuracy", "precision", "recall", "f1", "f1 weighted"], "tags": ["sentiment", "classification", "romanian", "nlp", "bert"], "model-index": [{"name": "ro-sentiment", "results": [{"task": {"t... | <!-- 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. -->
# RO-Sentiment
This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on t... | null | null | [
"decathlon_reviews",
"cinemagia_reviews"
] | [
"ro"
] | null | null | [
"accuracy",
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# nb-bert-base-ner
## Description
NB-Bert base model fine-tuned on the Named Entity Recognition task using the [NorNE dataset](https://huggingface.co/datasets/NbAiLab/norne).
## Usage
```python
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transform... | null | [
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<!-- header start -->
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The model is based on the T5 language model and trained using a large collection of movie descriptions and corresponding titles. When given a story it will generate a corresponding title.
## Usage
Example code:
```python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from... | null | [
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## Introduction
This repository provides the **AWQ 4-bit quantized** version of the **QwQ-32B-Preview** model, originally developed by the Qwen Team. The quantized model significantly reduces memory usage and computational requirements, making it suitable for deployment o... | null | [
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## Model Overview
Llama-3.3-Nemotron-Super-49B-v1 is a large language model (LLM) which is a derivative of [Meta Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) (AKA the *reference model*). It is a r... | null | [
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653f809f81f52ceb4d5cbb58 | 6ca12a20c4b51cfe | dfd094bbcec644b8 | 32,005 | BPE | 61,249 | true | false | true | true | 8 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 472 | datajuicer/LLaMA-1B-dj-refine-150B | datajuicer | null | 183,613 | 729,353 | False | 2023-10-30T10:08:31Z | 2023-11-10T10:20:45Z | transformers | 3 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | d897affaaa1b54a6388c2340e4d490ce27a485e1 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"dataset:datajuicer/redpajama-wiki-refined-by-data-juicer",
"dataset:datajuicer/redpajama-arxiv-refined-by-data-juicer",
"dataset:datajuicer/redpajama-c4-refined-by-data-juicer",
"dataset:datajuicer/redpajama-book-refined-by-data-juicer",
"datas... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<CLS>", "eos_token": "</s>", "mask_token": "<MASK>", "pad_token": "<PAD>", "sep_token": "<SEP>", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["datajuicer/redpajama-wiki-refined-by-data-juicer", "datajuicer/redpajama-arxiv-refined-by-data-juicer", "datajuicer/redpajama-c4-refined-by-data-juicer", "datajuicer/redpajama-book-refined-by-data-juicer", "datajuicer/redpajama-cc-2019-30-refined-by-data-juicer", "datajuicer/redpajama... | ## News
Our first data-centric LLM competition begins! Please visit the competition's official websites, **FT-Data Ranker** ([1B Track](https://tianchi.aliyun.com/competition/entrance/532157), [7B Track](https://tianchi.aliyun.com/competition/entrance/532158)), for more information.
## Introduction
This is a reference... | null | [
"apache-2.0"
] | [
"datajuicer/redpajama-wiki-refined-by-data-juicer",
"datajuicer/redpajama-arxiv-refined-by-data-juicer",
"datajuicer/redpajama-c4-refined-by-data-juicer",
"datajuicer/redpajama-book-refined-by-data-juicer",
"datajuicer/redpajama-cc-2019-30-refined-by-data-juicer",
"datajuicer/redpajama-cc-2020-05-refined-... | null | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68781234a5dbb701d7f4b8e9 | 6a67cbd79bab1e59 | cf1efbe71ef28fc9 | 50,368 | BPE | 50,009 | true | true | true | true | 116 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 395 | OpenMed/OpenMed-NER-SpeciesDetect-ModernMed-149M | OpenMed | null | 159,492 | 1,530,533 | False | 2025-07-16T20:57:24Z | 2025-08-05T09:42:13Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 149607171}, "total": 149607171} | [
".gitattributes",
"README.md",
"config.json",
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"special_tokens_map.json",
"test_results.json",
"tokenizer.json",
"tokenizer_config.json"
] | 326a76ee5259ac4e800b3875e29f601de6d599f2 | [
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"modernbert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"species-recognition",
"taxonomy",
"organism-identification",
"biology",
"species",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ModernBertForTokenClassification"], "model_type": "modernbert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | null | null | [
"apache-2.0"
] | null | [
"en"
] | 149,607,171 | null | null | [
"AutoModelForTokenClassification",
"ModernBertForTokenClassification",
"modernbert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
641955020841e29bbe175508 | d4d5f7cb385da884 | 2d4d455c0dc5b195 | 31,102 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 473 | nickprock/sentence-bert-base-italian-xxl-uncased | nickprock | null | 8,999 | 590,865 | False | 2023-03-21T06:56:02Z | 2025-03-14T08:47:24Z | sentence-transformers | 16 | 0 | null | sentence-similarity | {"parameters": {"I64": 512, "F32": 110695680}, "total": 110696192} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"onnx/model_qint8_avx512_vnni.onnx",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_conf... | 57f063ec6956120742337470a0d279b8ebf8fd2a | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"it",
"dataset:stsb_multi_mt",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["stsb_multi_mt"], "eval_results": null, "language": ["it"], "library_name": "sentence-transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extr... | # sentence-bert-base-italian-xxl-cased
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
It derives from [dbmdz/bert-base-italian-xxl-uncased](https://huggingface.co/dbmdz/... | null | [
"mit"
] | [
"stsb_multi_mt"
] | [
"it"
] | 110,696,192 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
689369249c8e12c7574ec8fe | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | lmstudio-community/Qwen3-4B-Instruct-2507-MLX-8bit | lmstudio-community | {
"models": [
{
"_id": "6891e3bb084ce75acffb033d",
"id": "Qwen/Qwen3-4B-Instruct-2507"
}
],
"relation": "quantized"
} | 58,456 | 802,513 | False | 2025-08-06T14:39:32Z | 2025-08-06T14:40:13Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 125892096, "U32": 1005568000}, "total": 1131460096} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 87618163944ec9e7976243481e41c9254a67da75 | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"mlx",
"conversational",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:quantized:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"8-bit",
"region:us"
] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "quantization_config": {"bits": 8}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'sy... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-4B-Instruct-2507", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_ta... | ## 💫 Community Model> Qwen3-4B-Instruct-2507 by Qwen
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [Qwen](https://huggingface.co/Qwen)<br>
**Origin... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE"
] | null | null | 1,131,460,096 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6231cbe55d6337b2758d7cc3 | 61cb272f6ac0ae3b | 8a01c02d4d0a401c | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 474 | krinal214/zero_shot | krinal214 | null | 4 | 532,209 | False | 2022-03-16T11:37:09Z | 2022-03-16T12:41:46Z | transformers | 0 | 0 | [{"name": "zero_last", "results": []}] | question-answering | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Mar16_11-37-00_6e036c0084cc/1647430633.948618/events.out.tfevents.1647430633.6e036c0084cc.34.1",
"runs/Mar16_11-37-00_6e036c0084cc/events.out.tfevents.1647430633.6e036c0084cc.34.0",
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"tok... | 50576657396ff78582c637891740e8add571e69d | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"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": ["squad"], "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "zero_last", "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. -->
# zero_last
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-case... | null | [
"apache-2.0"
] | [
"squad"
] | null | null | null | null | [
"AutoModelForQuestionAnswering",
"bert",
"BertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66854e52a24960c44dc70822 | 933915ee23663842 | ac8d046cbfff5b57 | 100,018 | BPE | 99,757 | true | true | true | true | 18 | Sequence | Sequence | ByteLevel | [] | [
"Split",
"Split",
"Split",
"Split",
"Split",
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 475 | casperhansen/deepseek-coder-v2-instruct-awq | casperhansen | null | 53,842 | 804,554 | False | 2024-07-03T13:12:50Z | 2024-07-03T15:16:38Z | transformers | 11 | 0 | null | text-generation | {"parameters": {"I32": 234643783680, "F16": 1097651200}, "total": 235741434880} | [
".gitattributes",
"README.md",
"config.json",
"configuration_deepseek.py",
"generation_config.json",
"model-00001-of-00026.safetensors",
"model-00002-of-00026.safetensors",
"model-00003-of-00026.safetensors",
"model-00004-of-00026.safetensors",
"model-00005-of-00026.safetensors",
"model-00006-of... | 3918bbb36a12d2a64e1f11a8079d71b0310f728c | [
"transformers",
"safetensors",
"deepseek_v2",
"text-generation",
"conversational",
"custom_code",
"arxiv:2401.06066",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"awq",
"region:us"
] | null | {"architectures": ["DeepseekV2ForCausalLM"], "auto_map": {"AutoConfig": "configuration_deepseek.DeepseekV2Config", "AutoModel": "modeling_deepseek.DeepseekV2Model", "AutoModelForCausalLM": "modeling_deepseek.DeepseekV2ForCausalLM"}, "model_type": "deepseek_v2", "quantization_config": {"bits": 4, "quant_method": "awq"},... | {
"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": "deepseek-license", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | <!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
# Quantized details
This model was quantized on 4x A100 80GB with 1TB system ram. It was quantized using the chosen preferences from the coding dataset of OpenHermes 2.5: https://huggingface.co/datasets/alvarobartt/openhermes-prefere... | null | [
"other",
"deepseek-license",
"LICENSE"
] | null | null | 235,741,434,880 | null | null | [
"AutoModelForCausalLM",
"DeepseekV2ForCausalLM",
"deepseek_v2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6829a2ceaa6207f7a62939eb | 63d0650f505ce8f9 | 0d1b0351a03fb052 | 200,029 | BPE | 199,742 | false | true | false | true | 12 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 207 | iqbalamo93/Phi-4-mini-instruct-GPTQ-8bit | iqbalamo93 | {
"models": [
{
"_id": "67b52d4a824d77f2bba8b0af",
"id": "microsoft/Phi-4-mini-instruct"
}
],
"relation": "quantized"
} | 14 | 530,552 | False | 2025-05-18T09:05:18Z | 2025-05-20T19:22:23Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"I32": 3221225472, "F16": 614796288}, "total": 3836021760} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | e05553799a1157fbe0b43a826a29952f9d6c63cc | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"nlp",
"code",
"GPTQ",
"conversational",
"custom_code",
"multilingual",
"ar",
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"nl",
"en",
"fi",
"fr",
"de",
"he",
"hu",
"it",
"ja",
"ko",
"no",
"pl",
"pt",
"ru",
"es",
"sv",
"th",
... | null | {"architectures": ["Phi3ForCausalLM"], "auto_map": {"AutoConfig": "microsoft/Phi-4-mini-instruct--configuration_phi3.Phi3Config", "AutoModelForCausalLM": "microsoft/Phi-4-mini-instruct--modeling_phi3.Phi3ForCausalLM", "AutoTokenizer": "microsoft/Phi-4-mini-instruct--Xenova/gpt-4o"}, "model_type": "phi3", "quantization_... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["microsoft/Phi-4-mini-instruct"], "datasets": null, "eval_results": null, "language": ["multilingual", "ar", "zh", "cs", "da", "nl", "en", "fi", "fr", "de", "he", "hu", "it", "ja", "ko", "no", "pl", "pt", "ru", "es", "sv", "th", "tr", "uk"], "library_name": "transformers", "license": "mit", "license_nam... | 🎉**Phi-4**: [[mini-reasoning](https://huggingface.co/microsoft/Phi-4-mini-reasoning) | [reasoning](https://huggingface.co/microsoft/Phi-4-reasoning)] | [[multimodal-instruct](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) | [onnx](https://huggingface.co/microsoft/Phi-4-multimodal-instruct-onnx)];
[[mini-... | null | [
"mit",
"https://huggingface.co/microsoft/Phi-4-mini-instruct/resolve/main/LICENSE"
] | null | [
"multilingual",
"ar",
"zh",
"cs",
"da",
"nl",
"en",
"fi",
"fr",
"de",
"he",
"hu",
"it",
"ja",
"ko",
"no",
"pl",
"pt",
"ru",
"es",
"sv",
"th",
"tr",
"uk"
] | 3,836,021,760 | null | null | [
"AutoModelForCausalLM",
"phi3",
"Phi3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
642f586e084ea70b373bca60 | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | pszemraj/long-t5-tglobal-base-sci-simplify | pszemraj | {
"models": [
{
"_id": "625aa30ce58e3083f52e0c64",
"id": "google/long-t5-tglobal-base"
}
],
"relation": "quantized"
} | 56 | 530,431 | False | 2023-04-06T23:40:30Z | 2025-12-29T03:43:02Z | transformers | 10 | 0 | null | summarization | {"parameters": {"F32": 247587456}, "total": 247587456} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.onnx",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | bf86a88089c7199d6dad4dc815ee4821e362070d | [
"transformers",
"pytorch",
"onnx",
"safetensors",
"longt5",
"text2text-generation",
"lay summaries",
"paper summaries",
"biology",
"medical",
"summarization",
"en",
"dataset:pszemraj/scientific_lay_summarisation-plos-norm",
"base_model:google/long-t5-tglobal-base",
"base_model:quantized:... | null | {"architectures": ["LongT5ForConditionalGeneration"], "model_type": "longt5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "google/long-t5-tglobal-base", "datasets": ["pszemraj/scientific_lay_summarisation-plos-norm"], "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": "summarizatio... | # long-t5-tglobal-base-sci-simplify
<a href="https://colab.research.google.com/gist/pszemraj/f0dc02c4d4a5c7ad1d5bf3953251145d/long-t5-tglobal-base-sci-simplify-plos-example-with-textsum.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
Exploring how well long-doc... | null | [
"apache-2.0"
] | [
"pszemraj/scientific_lay_summarisation-plos-norm"
] | [
"en"
] | 247,587,456 | null | null | [
"AutoModelForSeq2SeqLM",
"longt5",
"LongT5ForConditionalGeneration"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66793790ad156a21d11fd52a | 827f6451ef99df30 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 355 | Lajavaness/bilingual-embedding-large | Lajavaness | null | 7,625 | 791,031 | False | 2024-06-24T09:08:32Z | 2024-08-06T09:22:13Z | sentence-transformers | 27 | 0 | [{"name": "bilingual-embedding-large", "results": [{"task": {"type": "Clustering"}, "dataset": {"type": "lyon-nlp/alloprof", "name": "MTEB AlloProfClusteringP2P", "config": "default", "split": "test", "revision": "392ba3f5bcc8c51f578786c1fc3dae648662cb9b"}, "metrics": [{"type": "v_measure", "value": 65.3004467686438, "... | sentence-similarity | null | [
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"1_Pooling/.ipynb_checkpoints/config-checkpoint.json",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"sentence_bert_config.json",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.... | e83179d7a66e8aed1b3015e98bb5ae234ed89598 | [
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"safetensors",
"bilingual",
"feature-extraction",
"sentence-similarity",
"transformers",
"sentence-embedding",
"mteb",
"custom_code",
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"en",
"arxiv:2010.08240",
"arxiv:1911.02116",
"arxiv:1908.10084",
"license:apache-2.0",
"model-index",
"endpoints_compa... | null | {"architectures": ["BilingualModel"], "model_type": "bilingual", "auto_map": {"AutoConfig": "dangvantuan/bilingual_impl--config.BilingualConfig", "AutoModel": "dangvantuan/bilingual_impl--modeling.BilingualModel", "AutoModelForMaskedLM": "dangvantuan/bilingual_impl--modeling.BilingualForMaskedLM", "AutoModelForMultiple... | {
"auto_model": "AutoModel",
"custom_class": "dangvantuan/bilingual_impl--modeling.BilingualModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"language": ["fr", "en"], "library_name": "sentence-transformers", "license": "apache-2.0", "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers", "sentence-embedding", "mteb"], "model-index": [{"name": "bilingual-embedding-large", "results... | # [bilingual-embedding-large](https://huggingface.co/Lajavaness/bilingual-embedding-large)
Bilingual-embedding is the Embedding Model for bilingual language: french and english. This model is a specialized sentence-embedding trained specifically for the bilingual language, leveraging the robust capabilities of [XLM-Ro... | null | [
"apache-2.0"
] | null | [
"fr",
"en"
] | null | null | null | [
"BilingualModel",
"AutoModel",
"dangvantuan/bilingual_impl--modeling.BilingualModel",
"bilingual"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
689368e66aeae57256274f1b | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
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] | 47 | lmstudio-community/Qwen3-4B-Instruct-2507-MLX-6bit | lmstudio-community | {
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{
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],
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} | 57,571 | 792,693 | False | 2025-08-06T14:38:30Z | 2025-08-06T14:39:04Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 125892096, "U32": 754176000}, "total": 880068096} | [
".gitattributes",
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] | 9ea8c1e01dbccb3de7e3247309341b0cdf242cd7 | [
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"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "quantization_config": {"bits": 6}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'sy... | {
"auto_model": "AutoModelForCausalLM",
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} | {"base_model": "Qwen/Qwen3-4B-Instruct-2507", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_ta... | ## 💫 Community Model> Qwen3-4B-Instruct-2507 by Qwen
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [Qwen](https://huggingface.co/Qwen)<br>
**Origin... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE"
] | null | null | 880,068,096 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
689368a9ec7fe05a86c02e50 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | lmstudio-community/Qwen3-4B-Instruct-2507-MLX-5bit | lmstudio-community | {
"models": [
{
"_id": "6891e3bb084ce75acffb033d",
"id": "Qwen/Qwen3-4B-Instruct-2507"
}
],
"relation": "quantized"
} | 57,429 | 792,339 | False | 2025-08-06T14:37:29Z | 2025-08-06T14:37:58Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 125892096, "U32": 628480000}, "total": 754372096} | [
".gitattributes",
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] | 79af2310bd822b68249063ef2edd67671abc20d4 | [
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"text-generation",
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"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"5-bit",
"region:us"
] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "quantization_config": {"bits": 5}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'sy... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"base_model": "Qwen/Qwen3-4B-Instruct-2507", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_ta... | ## 💫 Community Model> Qwen3-4B-Instruct-2507 by Qwen
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [Qwen](https://huggingface.co/Qwen)<br>
**Origin... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE"
] | null | null | 754,372,096 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
663c854f4edaac49a8bc376f | 7ba26513ac305d8a | c21f0239d1cf0f86 | 65,024 | BPE | 64,784 | false | true | false | true | 13 | null | Sequence | ByteLevel | null | [
"Punctuation",
"ByteLevel",
"Digits",
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] | [
"ByteLevel"
] | 476 | tiiuae/falcon-11B | tiiuae | null | 5,299 | 558,083 | False | 2024-05-09T08:11:59Z | 2024-12-17T11:25:12Z | transformers | 218 | 0 | null | text-generation | {"parameters": {"BF16": 11102822400}, "total": 11102822400} | [
".gitattributes",
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"arxi... | null | {"architectures": ["FalconForCausalLM"], "auto_map": {"AutoConfig": "tiiuae/falcon-11B--configuration_falcon.FalconConfig", "AutoModel": "tiiuae/falcon-11B--modeling_falcon.FalconModel", "AutoModelForCausalLM": "tiiuae/falcon-11B--modeling_falcon.FalconForCausalLM", "AutoModelForQuestionAnswering": "tiiuae/falcon-11B--... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": ["tiiuae/falcon-refinedweb"], "eval_results": null, "language": ["en", "de", "es", "fr", "it", "nl", "pl", "pt", "ro", "cs"], "library_name": null, "license": "unknown", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, ... | # 🚀 Falcon2-11B
**Falcon2-11B is an 11B parameters causal decoder-only model built by [TII](https://www.tii.ae) and trained on over 5,000B tokens of [RefinedWeb](https://huggingface.co/datasets/tiiuae/falcon-refinedweb) enhanced with curated corpora. The model is made available under the [TII Falcon License 2.0](http... | null | [
"unknown"
] | [
"tiiuae/falcon-refinedweb"
] | [
"en",
"de",
"es",
"fr",
"it",
"nl",
"pl",
"pt",
"ro",
"cs"
] | 11,102,822,400 | null | null | [
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"falcon",
"FalconForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
657778ad4d989b0a6876e6da | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
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] | null | [
"Replace",
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] | 88 | TheBloke/Mixtral-8x7B-Instruct-v0.1-AWQ | TheBloke | {
"models": [
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"id": "mistralai/Mixtral-8x7B-Instruct-v0.1"
}
],
"relation": "quantized"
} | 9,388 | 580,739 | False | 2023-12-11T21:01:33Z | 2023-12-14T14:30:42Z | transformers | 59 | 0 | null | text-generation | {"parameters": {"I32": 46439333888, "F16": 263458816}, "total": 46702792704} | [
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"awq"... | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "quantization_config": {"bits": 4, "quant_method": "awq"}, "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false, "chat_template": "{{ bos_token }}{% for message in mess... | {
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} | {"base_model": "mistralai/Mixtral-8x7B-Instruct-v0.1", "datasets": null, "eval_results": null, "language": ["fr", "it", "de", "es", "en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "Mixtral 8X7B Instruct v0.1", "pipeline_tag": null, "tags":... | <!-- markdownlint-disable MD041 -->
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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<div style="display: flex; justify-content:... | null | [
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688a5f23e7cb4413ca5b8678 | b86074a73431b347 | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 434 | google/gemma-3-270m-it | google | {
"models": [
{
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}
],
"relation": "finetune"
} | 105,157 | 1,140,075 | manual | 2025-07-30T18:06:27Z | 2025-08-14T07:35:07Z | transformers | 567 | 1 | null | text-generation | null | [
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"auto_model": "AutoModelForCausalLM",
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} | {"base_model": "google/gemma-3-270m", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["gemma3", "gemma", "google"], "extra_gated_head... | null | null | [
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679a09e0fc4b676ca9103c6f | 36935258f89e8e9e | 83d37c6e8ee56b77 | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
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}
],
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} | 16,785 | 708,125 | False | 2025-01-29T10:58:40Z | 2025-04-09T20:58:27Z | transformers | 574 | 0 | null | text-generation | {"parameters": {"F32": 1777088000}, "total": 1777088000} | [
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} | {"base_model": ["deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"], "datasets": ["AI-MO/NuminaMath-CoT", "KbsdJames/Omni-MATH", "RUC-AIBOX/STILL-3-Preview-RL-Data", "hendrycks/competition_math"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": ... | null | null | [
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] | [
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] | [
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"ByteLevel"
] | [
"ByteLevel"
] | 62 | sentence-transformers/roberta-large-nli-stsb-mean-tokens | sentence-transformers | null | 9,546 | 579,080 | False | 2022-03-02T23:29:05Z | 2025-03-06T13:24:09Z | sentence-transformers | 1 | 0 | null | sentence-similarity | {"parameters": {"I64": 514, "F32": 355359744}, "total": 355360258} | [
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"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "sentence-transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction",... | **⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net - Pretrained Models](https://www.sbert.net/docs/pretrained_models.html)**
# sentence-transformers/roberta-large-nli-stsb-mean-tokens
This is a [sen... | null | [
"apache-2.0"
] | null | null | 355,360,258 | null | null | [
"roberta",
"AutoModel",
"RobertaModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
67f7f4815462e08b4e799b37 | b647996d6543f730 | 7ab62ce4e32550df | 151,674 | BPE | 151,387 | true | true | true | true | 31 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 172 | OpenGVLab/InternVL3-1B | OpenGVLab | {
"models": [
{
"_id": "67ff92c1a93c489f94ab29c6",
"id": "OpenGVLab/InternVL3-1B-Instruct"
}
],
"relation": "finetune"
} | 121,734 | 1,049,504 | False | 2025-04-10T16:40:33Z | 2025-09-11T12:49:40Z | transformers | 79 | 0 | null | image-text-to-text | {"parameters": {"BF16": 938193024}, "total": 938193024} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_intern_vit.py",
"configuration_internvl_chat.py",
"conversation.py",
"examples/image1.jpg",
"examples/image2.jpg",
"examples/red-panda.mp4",
"generation_config.json",
"merges.txt",
"model.safetensors",
"model... | 4415a3b810e636d11dfa86b0e9ba40bb00535aa8 | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"internvl",
"custom_code",
"image-text-to-text",
"conversational",
"multilingual",
"dataset:OpenGVLab/MMPR-v1.2",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.10442",
"arxiv:2504.10479",
"a... | null | {"architectures": ["InternVLChatModel"], "auto_map": {"AutoConfig": "configuration_internvl_chat.InternVLChatConfig", "AutoModel": "modeling_internvl_chat.InternVLChatModel", "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel"}, "model_type": "internvl_chat", "tokenizer_config": {"bos_token": null, "chat... | {
"auto_model": "AutoModel",
"custom_class": "modeling_internvl_chat.InternVLChatModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["OpenGVLab/InternVL3-1B-Instruct"], "datasets": ["OpenGVLab/MMPR-v1.2"], "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": n... | # InternVL3-1B
[\[📂 GitHub\]](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.co/paper... | null | [
"apache-2.0",
"qwen",
"https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE"
] | [
"OpenGVLab/MMPR-v1.2"
] | [
"multilingual"
] | 938,193,024 | null | null | [
"AutoModel",
"internvl_chat",
"InternVLChatModel",
"modeling_internvl_chat.InternVLChatModel"
] | [
"image-text-to-text",
"feature-extraction"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text",
"embeddings"
] |
658d93fd90b9c2cfa328a25b | 7419bc14a54f7dfc | 446a07780f0abc4c | 1,025 | BPE | 1,423 | true | true | false | true | 2 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Strip",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 477 | nvidia/parakeet-ctc-1.1b | nvidia | null | 974,178 | 3,122,373 | False | 2023-12-28T15:27:57Z | 2025-09-24T14:54:06Z | nemo | 42 | 1 | [{"name": "parakeet-ctc-1.1b", "results": [{"task": {"name": "Automatic Speech Recognition", "type": "automatic-speech-recognition"}, "dataset": {"name": "AMI (Meetings test)", "type": "edinburghcstr/ami", "config": "ihm", "split": "test", "args": {"language": "en"}}, "metrics": [{"name": "Test WER", "type": "wer", "va... | automatic-speech-recognition | null | [
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"preprocessor_config.json",
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"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | a707e818195cb97c8f7da2fc36b221a29f69a5db | [
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"en",
"dataset:librispeech_asr",
"dataset:fisher_corpus",
"dataset:Switchboard-1",
"dataset:WSJ-0"... | null | {"architectures": ["ParakeetForCTC"], "model_type": "parakeet_ctc", "tokenizer_config": {"pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForCTC",
"custom_class": null,
"pipeline_tag": "automatic-speech-recognition",
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} | {"datasets": ["librispeech_asr", "fisher_corpus", "Switchboard-1", "WSJ-0", "WSJ-1", "National-Singapore-Corpus-Part-1", "National-Singapore-Corpus-Part-6", "vctk", "voxpopuli", "europarl", "multilingual_librispeech", "mozilla-foundation/common_voice_8_0", "MLCommons/peoples_speech"], "language": ["en"], "library_name"... | null | null | [
"cc-by-4.0"
] | [
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"WSJ-0",
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"National-Singapore-Corpus-Part-1",
"National-Singapore-Corpus-Part-6",
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"europarl",
"multilingual_librispeech",
"mozilla-foundation/common_voice_8_0",
"MLCommons/peoples_speech"
] | [
"en"
] | null | null | [
"wer"
] | [
"parakeet_ctc",
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"AutoModelForCTC"
] | [
"automatic-speech-recognition"
] | [
"multimodal"
] | [
"audio"
] | [
"text"
] |
6888d1cf2d6ebec5b2845941 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | lmstudio-community/Qwen3-30B-A3B-Instruct-2507-MLX-4bit | lmstudio-community | {
"models": [
{
"_id": "6887274f2626398dc2e9f540",
"id": "Qwen/Qwen3-30B-A3B-Instruct-2507"
}
],
"relation": "quantized"
} | 40,912 | 715,104 | False | 2025-07-29T13:51:11Z | 2025-07-29T13:52:07Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"BF16": 954333184, "U32": 3816488960}, "total": 30532122624} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
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"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.i... | 22d11bad31cf8f3e01acd9fbb086026e143e5778 | [
"transformers",
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"text-generation",
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"license:apache-2.0",
"endpoints_compatible",
"4-bit",
"region:us"
] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "quantization_config": {"bits": 4}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-30B-A3B-Instruct-2507", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "p... | null | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507/blob/main/LICENSE"
] | null | null | 30,532,122,624 | null | null | [
"qwen3_moe",
"AutoModelForCausalLM",
"Qwen3MoeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
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] | [
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] |
661979ce8f38b0e3bafae23c | dc985383fab7a6fc | c81b23e1dcb12302 | 50,280 | BPE | 50,009 | true | true | true | true | 28 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 478 | allenai/OLMo-1B-hf | allenai | null | 28,878 | 625,955 | False | 2024-04-12T18:13:34Z | 2024-08-14T17:49:51Z | transformers | 27 | 1 | null | text-generation | {"parameters": {"F32": 1176764416}, "total": 1176764416} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | aee7752d9c08ee4775e9b0091426d8410e8f6a89 | [
"transformers",
"safetensors",
"olmo",
"text-generation",
"en",
"dataset:allenai/dolma",
"arxiv:2402.00838",
"arxiv:2302.13971",
"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}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["allenai/dolma"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | <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 1B
<!-- Provide a quick summary of what the model is/does. -->
OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the scie... | null | [
"apache-2.0"
] | [
"allenai/dolma"
] | [
"en"
] | 1,176,764,416 | null | null | [
"AutoModelForCausalLM",
"OlmoForCausalLM",
"olmo"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6897fbbec1c2503c0e2e7f47 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | xihc-ucb/Qwen3-8B-train-Quasar-0809 | xihc-ucb | null | 16 | 521,336 | False | 2025-08-10T01:54:06Z | 2025-08-20T01:52:14Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 8190735360}, "total": 8190735360} | [
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"chat_template.jinja",
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"model-00002-of-00004.safetensors",
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"model-00004-of-00004.safe... | eadc12463f163007ef25e010e9d53ffc0abfe3b2 | [
"transformers",
"safetensors",
"fp8_qwen3",
"text-generation",
"conversational",
"custom_code",
"arxiv:1910.09700",
"region:us"
] | null | {"architectures": ["FP8Qwen3ForCausalLM"], "auto_map": {"AutoConfig": "configuration_fp8_qwen3.FP8Qwen3Config", "AutoModel": "modeling_fp8_qwen3.FP8Qwen3Model", "AutoModelForCausalLM": "modeling_fp8_qwen3.FP8Qwen3ForCausalLM", "AutoModelForQuestionAnswering": "modeling_fp8_qwen3.FP8Qwen3ForQuestionAnswering", "AutoMode... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_fp8_qwen3.FP8Qwen3ForCausalLM",
"pipeline_tag": "text-generation",
"processor": null
} | {"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 | 8,190,735,360 | null | null | [
"AutoModelForCausalLM",
"FP8Qwen3ForCausalLM",
"fp8_qwen3",
"modeling_fp8_qwen3.FP8Qwen3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
677bf37d4fb3bc4007e9ddcf | 1e0a2493163c0c63 | 6622292dca275a2d | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 18 | Sao10K/70B-L3.3-Cirrus-x1 | Sao10K | {
"models": [
{
"_id": "6745f28f9333dfcc06268b1e",
"id": "meta-llama/Llama-3.3-70B-Instruct"
}
],
"relation": "finetune"
} | 12 | 521,790 | False | 2025-01-06T15:15:09Z | 2025-01-07T14:42:05Z | transformers | 41 | 0 | [{"name": "70B-L3.3-Cirrus-x1", "results": []}] | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"README.md",
"cloudy.png",
"config.json",
"model-00001-of-00012.safetensors",
"model-00002-of-00012.safetensors",
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"model-00005-of-00012.safetensors",
"model-00006-of-00012.safetensors",
"model-00007-of-0001... | 31d7ca33f3098d1eabe6f87a2c5b5bde85b20f35 | [
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"base_model:finetune:meta-llama/Llama-3.3-70B-Instruct",
"license:llama3.3",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["meta-llama/Llama-3.3-70B-Instruct"], "datasets": null, "eval_results": [], "language": null, "library_name": "transformers", "license": "llama3.3", "license_name": null, "license_link": null, "metrics": null, "model_name": "70B-L3.3-Cirrus-x1", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | 
# 70B-L3.3-Cirrus-x1
\- Same data composition as Freya, applied differently, trained longer too.
<br>\- Merging with its checkpoints was also involved.
<br>\- Has a nice style, with occasional issues that can be easily fixed.
<br>\- A m... | null | [
"llama3.3"
] | null | null | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65c386faa4c0603588024d4d | 160d831bbad97ece | 3a73b36e2f62ba5a | 40,960 | BPE | 66,500 | true | false | true | true | 4 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 479 | yanolja/YanoljaNEXT-EEVE-10.8B | yanolja | {
"models": [
{
"_id": "657874e50c22bb8984c717f7",
"id": "upstage/SOLAR-10.7B-v1.0"
}
],
"relation": "finetune"
} | 166 | 523,052 | False | 2024-02-07T13:34:50Z | 2025-08-29T03:54:05Z | transformers | 92 | 0 | [{"name": "yanolja/EEVE-Korean-10.8B-v1.0", "results": []}] | text-generation | {"parameters": {"BF16": 10804924416}, "total": 10804924416} | [
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"model-00005-of-00005.safetensors",
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"special_tokens_map... | 6c80bf97910d8e520fb26ee01f09d2bae76043cb | [
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"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'Yo... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "upstage/SOLAR-10.7B-v1.0", "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "yanolja/EEVE-Korean-10.8B-v1.0", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | null | null | [
"apache-2.0"
] | null | null | 10,804,924,416 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
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"text-generation"
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"text"
] | [
"text"
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"text"
] |
63e568ac3afbf4f1898338fe | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | EleutherAI/pythia-1.4b-deduped | EleutherAI | null | 10,099 | 565,941 | False | 2023-02-09T21:42:04Z | 2026-02-11T11:47:23Z | transformers | 21 | 0 | null | text-generation | {"parameters": {"F32": 1414647808}, "total": 1414647808} | [
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"pytorch_model.bin",
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] | 554d9c1bae3877f740aece41feb90f912cf9fedc | [
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"arxiv:2201.07311",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"depl... | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["EleutherAI/the_pile_deduplicated"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["pytorch", "causal-lm", "pythia"]} | The *Pythia Scaling Suite* is a collection of models developed to facilitate
interpretability research [(see paper)](https://arxiv.org/pdf/2304.01373.pdf).
It contains two sets of eight models of sizes
70M, 160M, 410M, 1B, 1.4B, 2.8B, 6.9B, and 12B. For each size, there are two
models: one trained on the Pile, and ... | null | [
"apache-2.0"
] | [
"EleutherAI/the_pile_deduplicated"
] | [
"en"
] | 1,414,647,808 | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66917420dd23665401bc5972 | f5e7f943c396c76b | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 52 | RedHatAI/Phi-3-medium-128k-instruct-quantized.w4a16 | RedHatAI | null | 1,231 | 523,093 | False | 2024-07-12T18:21:20Z | 2024-10-09T18:57:32Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"I64": 320, "I32": 1703936000, "BF16": 435246080}, "total": 2139182400} | [
".gitattributes",
"README.md",
"config.json",
"configuration_phi3.py",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"modeling_phi3.py",
"recipe.yaml",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_... | 8670dfac56d056b79944e6ab933f051a3cf4229d | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"conversational",
"custom_code",
"en",
"arxiv:2210.17323",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"compressed-tensors",
"region:us"
] | null | {"architectures": ["Phi3ForCausalLM"], "auto_map": {"AutoConfig": "configuration_phi3.Phi3Config", "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"}, "model_type": "phi3", "quantization_config": {"quant_method": "compressed-tensors"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in m... | {
"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": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | null | null | [
"llama2"
] | null | [
"en"
] | 2,139,182,400 | null | null | [
"AutoModelForCausalLM",
"phi3",
"Phi3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6693f5313774cc5e5c1d68ce | bafc5e0c20be7cd8 | 82d3db801e5d7f68 | 49,152 | BPE | 48,900 | false | true | false | true | 17 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 115 | HuggingFaceTB/SmolLM-1.7B | HuggingFaceTB | null | 67,289 | 738,091 | False | 2024-07-14T15:56:33Z | 2024-10-16T16:08:10Z | transformers | 181 | 0 | null | text-generation | {"parameters": {"F32": 1711376384}, "total": 1711376384} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"onnx/model.onnx",
"onnx/model.onnx_data",
"onnx/model_bnb4.onnx",
"onnx/model_fp16.onnx",
"onnx/model... | d7449ff7241c863f3e8accc475155f0f97afa011 | [
"transformers",
"onnx",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:HuggingFaceTB/smollm-corpus",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["HuggingFaceTB/smollm-corpus"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # SmolLM
<center>
<img src="https://huggingface.co/datasets/HuggingFaceTB/images/resolve/main/banner_smol.png" alt="SmolLM" width="1100" height="600">
</center>
## Table of Contents
1. [Model Summary](##model-summary)
2. [Limitations](##limitations)
3. [Training](##training)
4. [License](##license)
5. [Citation... | null | [
"apache-2.0"
] | [
"HuggingFaceTB/smollm-corpus"
] | [
"en"
] | 1,711,376,384 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
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] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 32 | google/t5-xl-lm-adapt | google | null | 30 | 514,452 | False | 2022-03-02T23:29:05Z | 2023-01-24T16:52:44Z | transformers | 14 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
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"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json"
] | f9843a55f0bdc37c957ddba20be0be4870b0a994 | [
"transformers",
"pytorch",
"tf",
"t5",
"text2text-generation",
"t5-lm-adapt",
"en",
"dataset:c4",
"arxiv:2002.05202",
"arxiv:1910.10683",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"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 | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 105 | TIGER-Lab/VLM2Vec-Full | TIGER-Lab | {
"models": [
{
"_id": "66bfe546a15b4eed7f6609a7",
"id": "microsoft/Phi-3.5-vision-instruct"
}
],
"relation": "finetune"
} | 88,558 | 800,477 | False | 2024-10-08T04:57:08Z | 2025-04-07T20:27:04Z | transformers | 29 | 0 | null | text-generation | {"parameters": {"BF16": 4146621440}, "total": 4146621440} | [
".gitattributes",
"README.md",
"config.json",
"configuration_phi3_v.py",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"modeling_phi3_v.py",
"preprocessor_config.json",
"processing_phi3_v.py",
"processor_config... | a0dcd8153e2563f1b39d80ae9afd71a4394773fb | [
"transformers",
"pytorch",
"safetensors",
"phi3_v",
"text-generation",
"Embedding",
"conversational",
"custom_code",
"en",
"dataset:TIGER-Lab/MMEB-train",
"arxiv:2410.05160",
"base_model:microsoft/Phi-3.5-vision-instruct",
"base_model:finetune:microsoft/Phi-3.5-vision-instruct",
"license:a... | null | {"architectures": ["Phi3VForCausalLM"], "auto_map": {"AutoConfig": "microsoft/Phi-3.5-vision-instruct--configuration_phi3_v.Phi3VConfig", "AutoModelForCausalLM": "microsoft/Phi-3.5-vision-instruct--modeling_phi3_v.Phi3VForCausalLM"}, "model_type": "phi3_v", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "microsoft/Phi-3.5-vision-instruct--modeling_phi3_v.Phi3VForCausalLM",
"pipeline_tag": "text-generation",
"processor": null
} | {"base_model": ["microsoft/Phi-3.5-vision-instruct"], "datasets": ["TIGER-Lab/MMEB-train"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["Embeddin... | # VLM2Vec
This repo contains the code and data for [VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks](https://arxiv.org/abs/2410.05160). In this paper, we aimed at building a unified multimodal embedding model for any tasks. Our model is based on converting an existing well-trained VLM (... | null | [
"apache-2.0"
] | [
"TIGER-Lab/MMEB-train"
] | [
"en"
] | 4,146,621,440 | null | [
"accuracy"
] | [
"AutoModelForCausalLM",
"Phi3VForCausalLM",
"microsoft/Phi-3.5-vision-instruct--modeling_phi3_v.Phi3VForCausalLM",
"phi3_v"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6641615dff178bd7ef60be60 | 31dabac8dc7ce889 | 7d900c9c71170270 | 257,153 | BPE | 580,604 | true | true | true | true | 218 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 138 | google/paligemma-3b-pt-448 | google | null | 1,046 | 517,562 | manual | 2024-05-13T00:39:57Z | 2024-07-19T12:10:14Z | transformers | 31 | 0 | null | image-text-to-text | {"parameters": {"F32": 2924351216}, "total": 2924351216} | [
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"README.md",
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"token... | b714490ff582c78fb13d35175505831497970a75 | [
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"arxiv:2103.01913",
"arxiv:2205.12522",
"arxiv:2110.11624",
"arxiv:2108.03353",
... | null | {"architectures": ["PaliGemmaForConditionalGeneration"], "model_type": "paligemma", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null, "extra_gated_heading": "Access PaliGemma on Hugging Face... | null | null | [
"gemma"
] | null | null | 2,924,351,216 | null | null | [
"PaliGemmaForConditionalGeneration",
"AutoModelForImageTextToText",
"paligemma"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
6554853ca4de813482f71db1 | 191e06b04083279c | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 26 | h-e-l-l-o/email-spam-classification-merged | h-e-l-l-o | null | 14 | 510,893 | False | 2023-11-15T08:45:48Z | 2024-01-09T05:53:08Z | transformers | 3 | 0 | null | text-classification | {"parameters": {"F32": 109483778}, "total": 109483778} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | b17c84ca4a36bc1b6c438031c7ec9a8bc0b36f9d | [
"transformers",
"safetensors",
"bert",
"text-classification",
"en",
"dataset:legacy107/spamming-email-classification",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["legacy107/spamming-email-classification"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "pipeline_tag": null, "tags": null} | null | null | [
"legacy107/spamming-email-classification"
] | [
"en"
] | 109,483,778 | null | [
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] | |
62ef658fb9958826ceefbe5e | 587dcb56b642ecae | 1c1343de013b8dd9 | 42,000 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 480 | joon09/kor-naver-ner-name | joon09 | null | 14 | 511,196 | False | 2022-08-07T07:11:11Z | 2023-04-04T05:25:50Z | transformers | 4 | 0 | null | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 2d8f6b4b4dd2cf124e9d000b9285064be276e71e | [
"transformers",
"pytorch",
"bert",
"token-classification",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | null | 한국인 이름 인식 모델
kor-bert fine-tuning 모델
자주 안쓰는 한글이름 기준으로
생성기를 만들어서, 16만개의 한글 이름을 생성 후 학습한 모델입니다.
ex) 안녕하세요. 임준영입니다. -> 안녕하세요. ***입니다.
```python
from transformers import BertTokenizerFast, BertForTokenClassification
from transformers import pipeline
model_name = 'joon09/kor-naver-ner-name'
tokenizer = BertTokenizerFa... | null | null | null | null | null | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
679242cc5ca3578ff4cf1ec4 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | Qwen/Qwen2.5-14B-Instruct-1M | Qwen | {
"models": [
{
"_id": "66e6d08a5c06b7719cebd8ec",
"id": "Qwen/Qwen2.5-14B"
}
],
"relation": "finetune"
} | 37,406 | 596,094 | False | 2025-01-23T13:23:24Z | 2025-01-29T12:38:27Z | transformers | 331 | 0 | null | text-generation | {"parameters": {"BF16": 14770033664}, "total": 14770033664} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00008.safetensors",
"model-00002-of-00008.safetensors",
"model-00003-of-00008.safetensors",
"model-00004-of-00008.safetensors",
"model-00005-of-00008.safetensors",
"model-00006-of-0... | 620fad32de7bdd2293b3d99b39eba2fe63e97438 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2501.15383",
"base_model:Qwen/Qwen2.5-14B",
"base_model:finetune:Qwen/Qwen2.5-14B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | 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/Qwen2.5-14B", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-1M/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "tex... | # Qwen2.5-14B-Instruct-1M
<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Introduction
Qwen2.5-1M is the long-context version of... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-1M/blob/main/LICENSE"
] | null | [
"en"
] | 14,770,033,664 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
689287fa5ca740ee917dee4a | 441f36ff7235b58e | 985b920c8f6b14f1 | 200,019 | BPE | 446,189 | false | true | true | true | 21 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 54 | lmstudio-community/gpt-oss-120b-MLX-8bit | lmstudio-community | {
"models": [
{
"_id": "68913522f16f3c8aaffccf1f",
"id": "openai/gpt-oss-120b"
}
],
"relation": "quantized"
} | 58,769 | 764,148 | False | 2025-08-05T22:38:50Z | 2025-08-06T00:08:35Z | transformers | 12 | 0 | null | text-generation | {"parameters": {"BF16": 3689969472, "U32": 29197209600}, "total": 116829154368} | [
".gitattributes",
"README.md",
"chat_template.jinja",
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"model-00003-of-00027.safetensors",
"model-00004-of-00027.safetensors",
"model-00005-of-00027.safetensors",
"model-00006-of-00027... | 1c030828424848835da935164c9e46a17241c577 | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"vllm",
"mlx",
"conversational",
"base_model:openai/gpt-oss-120b",
"base_model:quantized:openai/gpt-oss-120b",
"license:apache-2.0",
"endpoints_compatible",
"8-bit",
"region:us"
] | null | {"architectures": ["GptOssForCausalLM"], "model_type": "gpt_oss", "quantization_config": {"bits": 8}, "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|return|>", "pad_token": "<|endoftext|>"}, "chat_template_jinja": "{#-\n In addition to the normal inputs of `messages` and `tools`, this template al... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "openai/gpt-oss-120b", "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": ["vllm", "mlx"]} | ## 💫 Community Model> gpt-oss-120b by openai
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [openai](https://huggingface.co/openai)<br>
**Original m... | null | [
"apache-2.0"
] | null | null | 116,829,154,368 | null | null | [
"AutoModelForCausalLM",
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] | [
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] | [
"text"
] | [
"text"
] |
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"Split",
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"ByteLevel"
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{
"_id": "6887274f2626398dc2e9f540",
"id": "Qwen/Qwen3-30B-A3B-Instruct-2507"
}
],
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} | 34,374 | 692,784 | False | 2025-07-29T13:59:16Z | 2025-07-29T14:00:35Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"BF16": 954333184, "U32": 7632977920}, "total": 30532122624} | [
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"endpoints_compatible",
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"region:us"
] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "quantization_config": {"bits": 8}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-30B-A3B-Instruct-2507", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "p... | null | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507/blob/main/LICENSE"
] | null | null | 30,532,122,624 | null | null | [
"qwen3_moe",
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"text"
] | [
"text"
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6696a3096fa71ac401b70de0 | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 106 | princeton-nlp/gemma-2-9b-it-SimPO | princeton-nlp | {
"models": [
{
"_id": "667928d58601cd537f63c846",
"id": "google/gemma-2-9b-it"
}
],
"relation": "finetune"
} | 408 | 512,268 | False | 2024-07-16T16:42:49Z | 2024-08-02T22:04:11Z | transformers | 172 | 0 | [{"name": "princeton-nlp/gemma-2-9b-it-SimPO", "results": []}] | text-generation | {"parameters": {"BF16": 9241705984}, "total": 9241705984} | [
".gitattributes",
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"spec... | 8c87091f412e3aa6f74f66bd86c57fb81cbc3fde | [
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"arxiv:2310.01377",
"arxiv:2406.12845",
"base_model:google/gemma-2-9b-it",
"base_model:finetu... | null | {"architectures": ["Gemma2ForCausalLM"], "model_type": "gemma2", "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] | trim + '\n\n' %}{% set messages = messages[1:] %}{% else %}{% set system_message = '' %}{%... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "google/gemma-2-9b-it", "datasets": ["princeton-nlp/gemma2-ultrafeedback-armorm"], "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "princeton-nlp/gemma-2-9b-it-SimPO", "pipeline_tag": null, "tags": ["... | # gemma-2-9b-it-SimPO Model Card
SimPO (Simple Preference Optimization) is an offline preference optimization algorithm designed to enhance the training of large language models (LLMs) with preference optimization datasets. SimPO aligns the reward function with the generation likelihood, eliminating the need for a ref... | null | [
"mit"
] | [
"princeton-nlp/gemma2-ultrafeedback-armorm"
] | null | 9,241,705,984 | null | null | [
"AutoModelForCausalLM",
"gemma2",
"Gemma2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64827afc2e73ce18ad38e929 | 3a732ab237c338af | c21f0239d1cf0f86 | 65,024 | BPE | 64,784 | false | true | false | true | 12 | null | Sequence | ByteLevel | null | [
"Punctuation",
"ByteLevel",
"Digits",
"Split"
] | [
"ByteLevel"
] | 45 | vilsonrodrigues/falcon-7b-instruct-sharded | vilsonrodrigues | null | 10,168 | 556,376 | False | 2023-06-09T01:06:04Z | 2023-07-13T12:22:04Z | transformers | 26 | 0 | null | text-generation | {"parameters": {"F32": 6921720704}, "total": 6921720704} | [
".gitattributes",
"README.md",
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"... | 0e7ea20c0bfd0665eaf3835f1efd12a0e8f02d90 | [
"transformers",
"safetensors",
"falcon",
"text-generation",
"custom_code",
"en",
"dataset:tiiuae/falcon-refinedweb",
"arxiv:2205.14135",
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"arxiv:2005.14165",
"arxiv:2104.09864",
"arxiv:2306.01116",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatibl... | null | {"architectures": ["FalconForCausalLM"], "auto_map": {"AutoConfig": "configuration_falcon.FalconConfig", "AutoModel": "modeling_falcon.FalconModel", "AutoModelForSequenceClassification": "modeling_falcon.FalconForSequenceClassification", "AutoModelForTokenClassification": "modeling_falcon.FalconForTokenClassification",... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["tiiuae/falcon-refinedweb"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "inference": true, "widget": [{"text": "Hey Falcon!... | # Resharded
Resharded version of https://huggingface.co/tiiuae/falcon-7b-instruct for low RAM enviroments (e.g. Colab, Kaggle) in safetensors
Tutorial: https://medium.com/@vilsonrodrigues/run-your-private-llm-falcon-7b-instruct-with-less-than-6gb-of-gpu-using-4-bit-quantization-ff1d4ffbabcc
---
# ✨ Falcon-7B-Instr... | null | [
"apache-2.0"
] | [
"tiiuae/falcon-refinedweb"
] | [
"en"
] | 6,921,720,704 | null | null | [
"AutoModelForCausalLM",
"falcon",
"FalconForCausalLM"
] | [
"text-generation"
] | [
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"text"
] | [
"text"
] |
63875617189d6915f1d52bf6 | 019d2bc40e822f91 | c70f101c299b3fe1 | 31,006 | WordPiece | null | true | true | true | true | 9 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 481 | piuba-bigdata/beto-contextualized-hate-speech | piuba-bigdata | null | 9,131 | 534,082 | False | 2022-11-30T13:09:43Z | 2023-11-17T18:33:38Z | transformers | 7 | 0 | null | text-classification | {"parameters": {"I64": 512, "F32": 109860873}, "total": 109861385} | [
".gitattributes",
"README.md",
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"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | e9d7c2e72541d40679feef216b2f111e9ef64905 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"es",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["es"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["f1"], "model_name": null, "pipeline_tag": "text-classification", "tags": null} | ## Contextualized, fine-grained hate speech detection
Try our [demo]((https://huggingface.co/spaces/piubamas/discurso-de-odio).
Model trained to detect hate speech comments in news articles. Base model is BETO, a Spanish BERT pre-trained model. The task the model was trained on is a multilabel classification problem... | null | null | null | [
"es"
] | 109,861,385 | null | [
"f1"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
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"text-classification"
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"text"
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"text"
] | [
"logits"
] |
689bc3944b86fdeb37e9a08d | d9abafc9e84f6e37 | 298fb2136b26cee9 | 131,072 | BPE | 269,443 | false | true | true | true | 1,000 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 482 | nvidia/NVIDIA-Nemotron-Nano-9B-v2 | nvidia | {
"models": [
{
"_id": "68a677062fc955d300dc18f9",
"id": "nvidia/NVIDIA-Nemotron-Nano-12B-v2"
}
],
"relation": "finetune"
} | 437,365 | 1,355,153 | False | 2025-08-12T22:43:32Z | 2026-03-05T14:59:25Z | transformers | 484 | 1 | null | text-generation | {"parameters": {"BF16": 8888227328}, "total": 8888227328} | [
".gitattributes",
"README.md",
"acc-vs-budget.png",
"accuracy_chart.png",
"bias.md",
"config.json",
"configuration_nemotron_h.py",
"explainability.md",
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"model-00001-of-00004.safetensors",
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"model-00003-of-00004.safetensors",
"model... | 6533e8de2c68e4536bf7c411d7a3ce5734111476 | [
"transformers",
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"text-generation",
"nvidia",
"pytorch",
"conversational",
"custom_code",
"en",
"es",
"fr",
"de",
"it",
"ja",
"dataset:nvidia/Nemotron-Post-Training-Dataset-v1",
"dataset:nvidia/Nemotron-Post-Training-Dataset-v2",
"dataset:nvidia/Nemotron-P... | null | {"architectures": ["NemotronHForCausalLM"], "auto_map": {"AutoConfig": "configuration_nemotron_h.NemotronHConfig", "AutoModelForCausalLM": "modeling_nemotron_h.NemotronHForCausalLM"}, "model_type": "nemotron_h", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{%- set ns = namespace(enable_thinking=true) %}{%... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["nvidia/NVIDIA-Nemotron-Nano-12B-v2-Base", "nvidia/NVIDIA-Nemotron-Nano-12B-v2"], "datasets": ["nvidia/Nemotron-Post-Training-Dataset-v1", "nvidia/Nemotron-Post-Training-Dataset-v2", "nvidia/Nemotron-Pretraining-Dataset-sample", "nvidia/Nemotron-CC-v2", "nvidia/Nemotron-CC-Math-v1", "nvidia/Nemotron-Pre... | # NVIDIA-Nemotron-Nano-9B-v2
**Model Developer:** NVIDIA Corporation
**Model Dates:**
June 2025 \- August 2025
**Data Freshness:**
September 2024
The pretraining data has a cutoff date of September 2024.
## Model Overview
NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) tra... | null | [
"other",
"nvidia-open-model-license",
"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/"
] | [
"nvidia/Nemotron-Post-Training-Dataset-v1",
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"nvidia/Nemotron-Pretraining-Dataset-sample",
"nvidia/Nemotron-CC-v2",
"nvidia/Nemotron-CC-Math-v1",
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] | [
"en",
"es",
"fr",
"de",
"it",
"ja"
] | 8,888,227,328 | null | null | [
"AutoModelForCausalLM",
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"nemotron_h"
] | [
"text-generation"
] | [
"text"
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"text"
] | [
"text"
] |
624315aa44c9c3b21be72ddc | 9f7c7288cc977e30 | 30c0a02ad4ef2b27 | 32,100 | Unigram | null | true | true | true | true | 103 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 483 | UrukHan/t5-russian-spell | UrukHan | null | 7,498 | 532,825 | False | 2022-03-29T14:20:26Z | 2023-04-05T10:13:50Z | transformers | 34 | 0 | [{"name": "t5-russian-spell", "results": []}] | null | {"parameters": {"F32": 222903552}, "total": 222903552} | [
".gitattributes",
".gitignore",
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"runs/Apr01_18-47-32_604a29bdfffe/events.out.tfevents.1648839341.604a29bdfffe.74.0",
"runs/Apr... | 9f6acf7c1ace5137dcacb5d2d1f21cec3d312c69 | [
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"pytorch",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:UrukHan/wav2vec2-russian",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": "UrukHan/wav2vec2-russian", "eval_results": [], "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": "t5-russian-spell", "pipeline_tag": null, "tags": ["generated_from_trainer"], "widget": [{"text": "\u044b\u... | <!-- 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. -->
---
# t5-russian-spell
---
модель для исправление текста из распознаного аудио. моя модлеь для распознования аудио https://huggingf... | null | null | [
"UrukHan/wav2vec2-russian"
] | null | 222,903,552 | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
6888d2c4880501a5dde78f6a | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | lmstudio-community/Qwen3-30B-A3B-Instruct-2507-MLX-6bit | lmstudio-community | {
"models": [
{
"_id": "6887274f2626398dc2e9f540",
"id": "Qwen/Qwen3-30B-A3B-Instruct-2507"
}
],
"relation": "quantized"
} | 33,597 | 682,465 | False | 2025-07-29T13:55:16Z | 2025-07-29T13:56:20Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 954333184, "U32": 5724733440}, "total": 30532122624} | [
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"license:apache-2.0",
"endpoints_compatible",
"6-bit",
"region:us"
] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "quantization_config": {"bits": 6}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen3-30B-A3B-Instruct-2507", "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "p... | null | null | [
"apache-2.0",
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] | null | null | 30,532,122,624 | null | null | [
"qwen3_moe",
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] | [
"text-generation"
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] | [
"text"
] | [
"text"
] |
6750bb982861ac80bbbcaef7 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
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] | [
"Metaspace"
] | 28 | ibm-granite/granite-embedding-278m-multilingual | ibm-granite | null | 29,410 | 691,388 | False | 2024-12-04T20:29:12Z | 2025-08-19T01:36:37Z | transformers | 77 | 0 | [{"name": "ibm-granite/granite-embedding-278m-multilingual", "results": [{"dataset": {"config": "en-ext", "name": "MTEB AmazonCounterfactualClassification (en-ext)", "revision": "e8379541af4e31359cca9fbcf4b00f2671dba205", "split": "test", "type": "mteb/amazon_counterfactual"}, "metrics": [{"type": "accuracy", "value": ... | sentence-similarity | null | [
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"cs",
"de",
"es",
"fr",
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"ja",
"ko",
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"zh",
... | null | {"architectures": ["XLMRobertaModel"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": ... | {
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} | {"language": ["en", "ar", "cs", "de", "es", "fr", "it", "ja", "ko", "nl", "pt", "zh"], "library_name": "transformers", "license": "apache-2.0", "pipeline_tag": "sentence-similarity", "tags": ["language", "granite", "embeddings", "multilingual", "mteb", "sentence-transformers"], "model-index": [{"name": "ibm-granite/gra... | # Granite-Embedding-278m-multilingual
**Model Summary:**
Granite-Embedding-278M-Multilingual is a 278M parameter model from the Granite Embeddings suite that can be used to generate high quality text embeddings. This model produces embedding vectors of size 768 and is trained using a combination of open source relevan... | null | [
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] | d2c629e162c16be3a8ccc6e8e4a61405dde93cc2 | [
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"token-classification",
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"medical notes",
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"phi",
"en",
"dataset:I2B2",
"arxiv:1904.03323",
"license:mit",
"endpoints_compatible",
"deploy:azure",
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] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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} | {"base_model": null, "datasets": ["I2B2"], "eval_results": null, "language": ["en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": ["F1", "Recall", "AUC"], "model_name": null, "pipeline_tag": null, "tags": ["deidentification", "medical notes", "ehr", "phi"], "thumbnail":... | # Model Description
* A ClinicalBERT [[Alsentzer et al., 2019]](https://arxiv.org/pdf/1904.03323.pdf) model fine-tuned for de-identification of medical notes.
* Sequence Labeling (token classification): The model was trained to predict protected health information (PHI/PII) entities (spans). A list of protected health... | null | [
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} | 8,197 | 604,432 | False | 2024-09-25T19:39:36Z | 2024-12-10T02:49:13Z | transformers | 88 | 0 | null | image-text-to-text | {"parameters": {"BF16": 10670220835}, "total": 10670220835} | [
".gitattributes",
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"auto_model": "AutoModelForImageTextToText",
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} | {"base_model": "meta-llama/Llama-3.2-11B-Vision-Instruct", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "llama3.2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["llama-3", "llama", "meta", "faceb... | ## ***See [our collection](https://huggingface.co/collections/unsloth/vision-multimodal-models-673eb9908fc2cb3deebd2fa3) for vision models including Llama 3.2, Llava, Qwen2-VL and Pixtral.***
# Finetune Llama 3.2, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 not... | null | [
"llama3.2"
] | null | [
"en"
] | 10,670,220,835 | null | null | [
"AutoModelForImageTextToText",
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... | null | {"architectures": ["StableLmForCausalLM"], "model_type": "stablelm", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
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} | {"datasets": ["tiiuae/falcon-refinedweb", "togethercomputer/RedPajama-Data-1T", "CarperAI/pilev2-dev", "bigcode/starcoderdata", "allenai/peS2o"], "language": ["en"], "license": "cc-by-sa-4.0", "tags": ["causal-lm"], "model-index": [{"name": "stablelm-3b-4e1t", "results": [{"task": {"type": "text-generation", "name": "T... | # `StableLM-3B-4E1T`
## Model Description
`StableLM-3B-4E1T` is a 3 billion parameter decoder-only language model pre-trained on 1 trillion tokens of diverse English and code datasets for 4 epochs.
## Usage
Get started generating text with `StableLM-3B-4E1T` by using the following code snippet:
```python
from tran... | null | [
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<div style="text-align: center;">
<h1>Artigenz-Coder-DS-6.7B</h1>
<p>Artigenz team intends to create family of code generation models that can run very fast on local computers.</p>
<p>Artigenz-Coder-DS-6.7B is the... | null | [
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"dataset:indonlp/indonlu",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {"unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": fa... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["indonlp/indonlu"], "language": ["id"], "metrics": ["accuracy"], "tags": ["generated_from_trainer"], "widget": [{"text": "Entah mengapa saya merasakan ada sesuatu yang janggal di produk ini"}], "model-index": [{"name": "roberta-base-indonesian-1.5G-sentiment-analysis-smsa", "results": [{"task": {"type": "... | <!-- 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-indonesian-1.5G-sentiment-analysis-smsa
This model is a fine-tuned version of [cahya/roberta-base-indonesian-1.5G](h... | null | null | [
"indonlp/indonlu"
] | [
"id"
] | null | null | [
"accuracy"
] | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
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