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"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 342 | unsloth/gemma-3n-E4B-it-unsloth-bnb-4bit | unsloth | {
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{
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"id": "google/gemma-3n-E4B-it"
}
],
"relation": "quantized"
} | 8,355 | 270,548 | False | 2025-06-26T15:01:20Z | 2025-07-11T04:22:42Z | transformers | 9 | 0 | null | image-text-to-text | {"parameters": {"F32": 335712, "BF16": 3913886032, "U8": 4059214596}, "total": 7849978192} | [
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] | null | [
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] | [
"text",
"image"
] | [
"text"
] |
680f891f1b2ee440399b274c | 46323c0f61df476d | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 49 | RedHatAI/gemma-3-27b-it-FP8-dynamic | RedHatAI | {
"models": [
{
"_id": "67c35b9bb236f0d365bf29d3",
"id": "google/gemma-3-27b-it"
}
],
"relation": "quantized"
} | 18,578 | 281,461 | False | 2025-04-28T13:56:47Z | 2025-06-09T15:12:26Z | transformers | 13 | 1 | null | image-text-to-text | {"parameters": {"BF16": 1837886064, "F8_E4M3": 25598361600}, "total": 27436247664} | [
".gitattributes",
"Notice",
"README.md",
"added_tokens.json",
"chat_template.json",
"config.json",
"generation_config.json",
"model-00001-of-00006.safetensors",
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"model-00004-of-00006.safetensors",
"model-00005-of-00006.saf... | 306078afe860ef87821018f28078ecf762f31455 | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"vllm",
"vision",
"fp8",
"conversational",
"en",
"base_model:google/gemma-3-27b-it",
"base_model:quantized:google/gemma-3-27b-it",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"compressed-tensors... | null | {"architectures": ["Gemma3ForConditionalGeneration"], "model_type": "gemma3", "quantization_config": {"quant_method": "compressed-tensors"}, "processor_config": {"chat_template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n {%- if messages[0]['content'] is string -%}\n {%- set first_user_pre... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": "google/gemma-3-27b-it", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md", "metrics": null, "model_name": nu... | # gemma-3-27b-it-FP8-Dynamic
## Model Overview
- **Model Architecture:** gemma-3-27b-it
- **Input:** Vision-Text
- **Output:** Text
- **Model Optimizations:**
- **Weight quantization:** FP8
- **Activation quantization:** FP8
- **Release Date:** 2/24/2025
- **Version:** 1.0
- **Model Developers:** Neural Magic
... | null | [
"apache-2.0",
"https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md"
] | null | [
"en"
] | 27,436,247,664 | null | null | [
"AutoModelForImageTextToText",
"Gemma3ForConditionalGeneration",
"gemma3"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
67d2cbc2564d179e1382a929 | 46323c0f61df476d | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 49 | unsloth/gemma-3-27b-it-unsloth-bnb-4bit | unsloth | {
"models": [
{
"_id": "67c35b9bb236f0d365bf29d3",
"id": "google/gemma-3-27b-it"
}
],
"relation": "quantized"
} | 5,071 | 247,477 | False | 2025-03-13T12:12:50Z | 2025-05-12T08:06:49Z | transformers | 19 | 0 | null | image-text-to-text | {"parameters": {"F32": 1543424, "BF16": 3981004400, "U8": 24184400918}, "total": 28166948742} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
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"config.json",
"generation_config.json",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005... | 6ffe669a86fe697aef8ee7b46f5a77477d2a1ddd | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"unsloth",
"gemma",
"google",
"conversational",
"en",
"arxiv:1905.07830",
"arxiv:1905.10044",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1705.03551",
"arxiv:1911.01547",
"arxiv:1907.10641",
"arxiv:1903.00161",
"arxi... | null | {"architectures": ["Gemma3ForConditionalGeneration"], "model_type": "gemma3", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "processor_config": {"chat_template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n {%- if messages[0]['content'] is str... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": "google/gemma-3-27b-it", "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "transformers", "gemma3", "gemma", "google"]} | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/gemma-3-67d12b7e8816ec6efa7e4e5b">our collection</a> for all versions of Gemma 3 including GGUF, 4-bit & 16-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em>Unsloth's <a href="htt... | null | [
"gemma"
] | null | [
"en"
] | 28,166,948,742 | null | null | [
"AutoModelForImageTextToText",
"Gemma3ForConditionalGeneration",
"gemma3"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
65b34ec5d1164871bea200ed | 099efed77b535bd4 | c81b23e1dcb12302 | 50,280 | BPE | 50,009 | true | true | true | true | 28 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 616 | allenai/OLMo-1B | allenai | null | 3,655 | 209,336 | False | 2024-01-26T06:18:45Z | 2024-07-16T18:02:54Z | transformers | 107 | 0 | null | text-generation | {"parameters": {"F32": 1176764416}, "total": 1176764416} | [
".gitattributes",
"README.md",
"config.json",
"configuration_olmo.py",
"model.safetensors",
"modeling_olmo.py",
"pytorch_model.bin",
"requirements.txt",
"revisions.txt",
"special_tokens_map.json",
"tokenization_olmo_fast.py",
"tokenizer.json",
"tokenizer_config.json"
] | 344d48f1ef038097ed9471da33ddf2721e59f474 | [
"transformers",
"pytorch",
"safetensors",
"hf_olmo",
"text-generation",
"custom_code",
"en",
"dataset:allenai/dolma",
"arxiv:2402.00838",
"arxiv:2302.13971",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["OLMoForCausalLM"], "model_type": "hf_olmo", "auto_map": {"AutoConfig": "configuration_olmo.OLMoConfig", "AutoModelForCausalLM": "modeling_olmo.OLMoForCausalLM"}, "tokenizer_config": {"eos_token": "<|endoftext|>", "pad_token": "<|padding|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_olmo.OLMoForCausalLM",
"pipeline_tag": "text-generation",
"processor": null
} | {"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. -->
**For transformers versions v4.40.0 or newer, we suggest using [OLMo 1B HF](http... | null | [
"apache-2.0"
] | [
"allenai/dolma"
] | [
"en"
] | 1,176,764,416 | null | null | [
"modeling_olmo.OLMoForCausalLM",
"AutoModelForCausalLM",
"hf_olmo",
"OLMoForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
689ecb6623e9b8c9387d224c | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | AIDC-AI/Ovis2.5-2B | AIDC-AI | null | 114,687 | 565,268 | False | 2025-08-15T05:53:42Z | 2026-02-13T03:18:04Z | transformers | 200 | 0 | null | image-text-to-text | {"parameters": {"BF16": 2570429672}, "total": 2570429672} | [
".gitattributes",
"LICENSE",
"NOTICE",
"README.md",
"added_tokens.json",
"chat_template.json",
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"configuration_ovis2_5.py",
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"merges.txt",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"modelin... | 393c932b2a03e28eb9aaa503e3c4ab3ad384d958 | [
"transformers",
"safetensors",
"ovis2_5",
"text-generation",
"MLLM",
"image-text-to-text",
"conversational",
"custom_code",
"en",
"zh",
"dataset:AIDC-AI/Ovis-dataset",
"arxiv:2508.11737",
"arxiv:2405.20797",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["Ovis2_5"], "auto_map": {"AutoConfig": "configuration_ovis2_5.Ovis2_5_Config", "AutoModelForCausalLM": "modeling_ovis2_5.Ovis2_5"}, "model_type": "ovis2_5", "processor_config": {"chat_template": "{%- for message in messages %}{{- '<|im_start|>' + message.role + '\n'}}{%- if message.role == 'system' o... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_ovis2_5.Ovis2_5",
"pipeline_tag": "text-generation",
"processor": null
} | {"base_model": null, "datasets": ["AIDC-AI/Ovis-dataset"], "eval_results": null, "language": ["en", "zh"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ["MLLM"]} | # Ovis2.5-2B
<div align="center">
<img src=https://cdn-uploads.huggingface.co/production/uploads/637aebed7ce76c3b834cea37/3IK823BZ8w-mz_QfeYkDn.png width="30%"/>
</div>
<p align="center">
<a href="https://arxiv.org/abs/2508.11737"><img src="https://img.shields.io/badge/📖_Technical_Report-Ovis2.5-b31b1b.svg" alt="... | null | [
"apache-2.0"
] | [
"AIDC-AI/Ovis-dataset"
] | [
"en",
"zh"
] | 2,570,429,672 | null | null | [
"AutoModelForCausalLM",
"Ovis2_5",
"modeling_ovis2_5.Ovis2_5",
"ovis2_5"
] | [
"image-text-to-text",
"text-generation"
] | [
"text",
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
62429364cce0bae7eb47a9f4 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | Intel/distilbert-base-uncased-finetuned-sst-2-english-int8-static-inc | Intel | null | 381 | 197,616 | False | 2022-03-29T05:04:36Z | 2023-06-27T08:21:13Z | transformers | 6 | 0 | [{"name": "distilbert-base-uncased-finetuned-sst-2-english-int8-static", "results": [{"task": {"type": "sentiment-classification", "name": "Sentiment Classification"}, "dataset": {"type": "sst2", "name": "Stanford Sentiment Treebank"}, "metrics": [{"type": "accuracy", "value": 90.37, "name": "accuracy", "config": "accu... | text-classification | null | [
".gitattributes",
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"config.json",
"model.onnx",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | bc1fc91ebe84493fdd44db19751fab7877779d02 | [
"transformers",
"pytorch",
"onnx",
"distilbert",
"text-classification",
"text-classfication",
"int8",
"neural-compressor",
"Intel® Neural Compressor",
"PostTrainingStatic",
"en",
"dataset:sst2",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
... | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["sst2"], "language": "en", "license": "apache-2.0", "tags": ["text-classfication", "int8", "neural-compressor", "Intel\u00ae Neural Compressor", "PostTrainingStatic"], "model-index": [{"name": "distilbert-base-uncased-finetuned-sst-2-english-int8-static", "results": [{"task": {"type": "sentiment-classific... | ## Model Details: INT8 DistilBERT base uncased finetuned SST-2
This model is a fine-tuned DistilBERT model for the downstream task of sentiment classification, training on the [SST-2 dataset](https://huggingface.co/datasets/sst2) and quantized to INT8 (post-training static quantization) from the original FP32 model ([... | null | [
"apache-2.0"
] | [
"sst2"
] | [
"en"
] | null | null | null | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | maxcurrent/Peagle-9b | maxcurrent | null | 12,791 | 257,175 | False | 2024-03-10T17:35:17Z | 2024-05-21T12:53:12Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"F16": 8986628096}, "total": 8986628096} | [
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"model-0000... | 26e8229dbfb6c12d70ea7be34699c8007ad75228 | [
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"mistral",
"text-generation",
"merge",
"mergekit",
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"mlabonne/NeuralBeagle14-7B",
"eldogbbhed/NeuralPearlBeagle",
"conversational",
"license:cc-by-nc-4.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{{bos_token + message['role'] + '\n' + message['content'] + eos_token + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ bos_token + 'assistant\n' }}{% endif %}", ... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["merge", "mergekit", "vortexmergekit", "mlabonne/NeuralBeagle14-7B", "eldogbbhed... | null | null | [
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] | null | null | 8,986,628,096 | null | null | [
"AutoModelForCausalLM",
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] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Split",
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"bamba",
"text-generation",
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<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated... | null | null | null | null | 33,110,760 | null | null | [
"BambaForCausalLM",
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The MVP-open-dialog model was proposed in [**MVP: Multi-task Supervised Pre-training for Natural Language Generation**](https://arxiv.org/abs/2206.12131) by Tianyi Tang, Junyi Li, Wayne Xin Zhao and Ji-Rong Wen.
The detailed information and instructions can be found [https://github.com/RUCAIBox/MVP](... | null | [
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**luke-japanese** is the Japanese version of **LUKE** (**L**anguage
**U**nderstanding with **K**nowledge-based **E**mbeddings), a pre-trained
_knowledge-enhanced_ contextualized representation of words and entities. LUKE
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UL2 is a unified framework for pretraining models that are universally effective across datasets and setups. UL2 uses Mixture-of-Denoisers (MoD), apre-training objective that combines diverse pre-training paradigms together. UL2 introduces a notion of mode switching, wherein downstream fine-tuning is as... | null | [
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"rela... | 124 | 209,676 | False | 2024-04-22T05:07:13Z | 2024-06-02T08:18:10Z | transformers | 40 | 0 | [{"name": "Medichat-Llama3-8B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 59.13, "name": "no... | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
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"dataset:jondurbin/airoboros-3.2",
"dataset:microsoft/orca-math-word-problems-200k",
"dataset:m-a-p/Co... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{%- set ns = namespace(found=false) -%}{%- for message in messages -%}{%- if message['role'] == 'system' -%}{%- set ns.found = true -%}{%- endif -%}{%- endfor -%}{%- for message in mes... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Undi95/Llama-3-Unholy-8B", "Locutusque/llama-3-neural-chat-v1-8b", "ruslanmv/Medical-Llama3-8B-16bit"], "datasets": ["mlabonne/orpo-dpo-mix-40k", "Open-Orca/SlimOrca-Dedup", "jondurbin/airoboros-3.2", "microsoft/orca-math-word-problems-200k", "m-a-p/Code-Feedback", "MaziyarPanahi/WizardLM_evol_instruct... | ### Medichat-Llama3-8B
Built upon the powerful LLaMa-3 architecture and fine-tuned on an extensive dataset of health information, this model leverages its vast medical knowledge to offer clear, comprehensive answers.
This model is generally better for accurate and informative responses, particularly for users seeking... | null | [
"other"
] | [
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"MaziyarPanahi/WizardLM_evol_instruct_V2_196k",
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"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 37 | OpenMed/OpenMed-NER-ProteinDetect-TinyMed-66M | OpenMed | null | 90,909 | 524,468 | False | 2025-07-18T09:01:05Z | 2025-08-05T09:45:32Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 66371339}, "total": 66371339} | [
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"special_tokens_map.json",
"test_results.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 2d73e191750efc048239ef51a13db165b7952dd5 | [
"transformers",
"safetensors",
"distilbert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"protein-interactions",
"molecular-biology",
"biochemistry",
"systems-biology",
"protein",
"protein_complex",
"protein_enum",
"protein_familiy_or_group",
"protein_variant",
... | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-ProteinDetect-TinyMed-66M](https://huggingface.co/OpenMed/OpenMed-NER-ProteinDetect-TinyMed-66M)
**Specialized model for Biomedical Entity Recognition - Various biomedical entities**
[](https://opensource.org/licenses/Apache-2.0)
... | null | [
"apache-2.0"
] | null | [
"en"
] | 66,371,339 | null | null | [
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"DistilBertForTokenClassification"
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687a0ddcb05ce8c9bcc34386 | 5b8a6156b5b6e013 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
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"vocab.txt"
] | 90cbac7f43d0c16e9b4df2a177e451eee1a3dff5 | [
"transformers",
"safetensors",
"bert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"chemical-entity-recognition",
"drug-discovery",
"pharmacology",
"chemistry",
"chem",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-ChemicalDetect-ElectraMed-109M](https://huggingface.co/OpenMed/OpenMed-NER-ChemicalDetect-ElectraMed-109M)
**Specialized model for Chemical Entity Recognition - Identifies chemical compounds and substances in biomedical literature**
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.... | null | [
"apache-2.0"
] | null | [
"en"
] | 108,893,955 | null | null | [
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"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
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"Precompiled"
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"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 230 | OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M | OpenMed | null | 89,450 | 519,011 | False | 2025-07-18T09:10:24Z | 2025-08-05T09:46:14Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 277455363}, "total": 277455363} | [
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] | 443b2ac7552bdebb46d31ac5cef8ac2cd2f6a04a | [
"transformers",
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"xlm-roberta",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"gene-recognition",
"protein-recognition",
"genomics",
"molecular-biology",
"gene/protein",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"regio... | null | {"architectures": ["XLMRobertaForTokenClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-GenomeDetect-BigMed-278M](https://huggingface.co/OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M)
**Specialized model for Gene/Protein Entity Recognition - Gene and protein mentions**
[](https://opensource.org/licenses/Apache-2.0)
[!... | null | [
"apache-2.0"
] | null | [
"en"
] | 277,455,363 | null | null | [
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] | [
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] | [
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"ByteLevel"
] | 658 | OpenMed/OpenMed-NER-DNADetect-EuroMed-212M | OpenMed | null | 89,795 | 518,297 | False | 2025-07-18T08:46:49Z | 2025-08-05T09:44:32Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 211774475}, "total": 211774475} | [
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"arxiv:2508.01630",
... | null | {"architectures": ["EuroBertForTokenClassification"], "auto_map": {"AutoConfig": "configuration_eurobert.EuroBertConfig", "AutoModel": "modeling_eurobert.EuroBertModel", "AutoModelForMaskedLM": "modeling_eurobert.EuroBertForMaskedLM", "AutoModelForPreTraining": "modeling_eurobert.EuroBertPreTrainedModel", "AutoModelFor... | {
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] | 211,774,475 | null | null | [
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] | be265ad79b5541e3af5d4bdda314822fcaccb884 | [
"transformers",
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"biomedical-nlp",
"gene-recognition",
"genetics",
"genomics",
"molecular-biology",
"cell-line-name",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-GenomicDetect-ElectraMed-109M](https://huggingface.co/OpenMed/OpenMed-NER-GenomicDetect-ElectraMed-109M)
**Specialized model for Gene Entity Recognition - Gene-related entities**
[](https://opensource.org/licenses/Apache-2.0)
[![P... | null | [
"apache-2.0"
] | null | [
"en"
] | 108,893,955 | null | null | [
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"bert"
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"token-classification"
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] | [
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"WhitespaceSplit",
"Metaspace"
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"Metaspace"
] | 230 | OpenMed/OpenMed-NER-OncologyDetect-ElectraMed-560M | OpenMed | null | 21 | 415,978 | False | 2025-07-18T09:05:55Z | 2025-08-05T09:45:55Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 558874657}, "total": 558874657} | [
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] | f2590c17adddebbf91b666aaf5de99ebcc816869 | [
"transformers",
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"xlm-roberta",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"cancer-genetics",
"oncology",
"gene-regulation",
"cancer-research",
"amino_acid",
"anatomical_system",
"cancer",
"cell",
"cellular_component",
"developing_anatomical_str... | null | {"architectures": ["XLMRobertaForTokenClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-OncologyDetect-ElectraMed-560M](https://huggingface.co/OpenMed/OpenMed-NER-OncologyDetect-ElectraMed-560M)
**Specialized model for Cancer Genetics - Cancer-related genetic entities**
[](https://opensource.org/licenses/Apache-2.0)
... | null | [
"apache-2.0"
] | null | [
"en"
] | 558,874,657 | null | null | [
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"text"
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687a0f1de10ebcd02033ae65 | 247b76e6aa48f448 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
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"ByteLevel"
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] | adbe4f376277ae554defb9be04d5347a140ab916 | [
"transformers",
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"roberta",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"gene-recognition",
"genetics",
"genomics",
"molecular-biology",
"cell-line-name",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForTokenClassification"], "model_type": "roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-GenomicDetect-SuperMedical-355M](https://huggingface.co/OpenMed/OpenMed-NER-GenomicDetect-SuperMedical-355M)
**Specialized model for Gene Entity Recognition - Gene-related entities**
[](https://opensource.org/licenses/Apache-2.0)
... | null | [
"apache-2.0"
] | null | [
"en"
] | 354,313,219 | null | null | [
"roberta",
"AutoModelForTokenClassification",
"RobertaForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
687813ec700eb6e8daea4e83 | 6a67cbd79bab1e59 | cf1efbe71ef28fc9 | 50,368 | BPE | 50,009 | true | true | true | true | 116 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 395 | OpenMed/OpenMed-NER-ProteinDetect-ModernMed-149M | OpenMed | null | 89,502 | 516,554 | False | 2025-07-16T21:04:44Z | 2025-08-05T09:42:43Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 149613323}, "total": 149613323} | [
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"tokenizer_config.json"
] | 32ceccffbb58b233cea31f4c1e570f7ecd74da8c | [
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"protein-interactions",
"molecular-biology",
"biochemistry",
"systems-biology",
"protein",
"protein_complex",
"protein_enum",
"protein_familiy_or_group",
"protein_variant",
... | 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",
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} | {"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"
] | 149,613,323 | null | null | [
"AutoModelForTokenClassification",
"ModernBertForTokenClassification",
"modernbert"
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"token-classification"
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"text"
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"en",
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] | null | {"architectures": ["GPTJForCausalLM"], "model_type": "gptj", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized"... | {
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} | {"base_model": null, "datasets": ["nomic-ai/gpt4all-j-prompt-generations"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | # Model Card for GPT4All-J
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. -->
This model has been ... | null | [
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] | 8589ecab3fc4dc25d78e1ae213a3fc7f978de0a5 | [
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"... | null | {"architectures": ["RobertaForTokenClassification"], "model_type": "roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
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**Specialized model for Biomedical Entity Recognition - Various biomedical entities**
[](https://opensource.org/licenses/... | null | [
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This model has been finetuned with SecureBERT (https://arxiv.org/abs/2204.02685)
on the APTNER dataset (https://ieeexplore.ieee.org/document/9776031)
## NER Classes
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"Split",
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"... | 347a2e393f548790707283151105ea15aebdd4e7 | [
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"arxiv:2405.07863",
"arxiv:2312.11456",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|start_header_id|>' + message['role'] + '<|end_header_id... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | # SFR-Iterative-DPO-Llama-3-8B-R
## Introduction
We release a state-of-the-art instruct model of its class, **SFR-Iterative-DPO-LLaMA-3-8B-R**.
On all three widely-used instruct model benchmarks: **Alpaca-Eval-V2**, **MT-Bench**, **Chat-Arena-Hard**, our model outperforms all models of similar size (e.g., LLaMA-3-8B-i... | null | null | null | null | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
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"text-generation"
] | [
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] | [
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] | [
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] | 723 | KoichiYasuoka/bert-base-japanese-upos | KoichiYasuoka | {
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"id": "KoichiYasuoka/bert-base-japanese-char-extended"
}
],
"relation": "finetune"
} | 64 | 195,653 | False | 2022-03-02T23:29:04Z | 2026-01-21T13:38:19Z | transformers | 2 | 0 | null | token-classification | null | [
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## Model Description
This is a BERT model pre-trained on Japanese Wikipedia texts for POS-tagging and dependency-parsing, derived from [bert-base-japanese-char-extended](https://huggingface.co/KoichiYasuoka/bert-base-japanese-char-extended). Every short-unit-word is tagged by [UPOS](https://... | null | [
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
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"region:us"
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"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-ChemicalDetect-SuperMedical-125M](https://huggingface.co/OpenMed/OpenMed-NER-ChemicalDetect-SuperMedical-125M)
**Specialized model for Chemical Entity Recognition - Identifies chemical compounds and substances in biomedical literature**
[![License](https://img.shields.io/badge/License-Apache%202.0-b... | null | [
"apache-2.0"
] | null | [
"en"
] | 124,057,347 | null | null | [
"roberta",
"AutoModelForTokenClassification",
"RobertaForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
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"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
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] | 8917a1ceb9ae7353d6775bbf0584f77f010eb766 | [
"transformers",
"safetensors",
"xlm-roberta",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"anatomical-entity-recognition",
"medical-terminology",
"anatomy",
"healthcare",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["XLMRobertaForTokenClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-AnatomyDetect-BigMed-278M](https://huggingface.co/OpenMed/OpenMed-NER-AnatomyDetect-BigMed-278M)
**Specialized model for Anatomical Entity Recognition - Anatomical structures and body parts**
[](https://opensource.org/licenses/Apa... | null | [
"apache-2.0"
] | null | [
"en"
] | 277,455,363 | null | null | [
"XLMRobertaForTokenClassification",
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"BertPreTokenizer"
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] | 83c597b1095a2d880334f5cad6c65e2a6bfa0d55 | [
"transformers",
"safetensors",
"bert",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"disease-entity-recognition",
"medical-diagnosis",
"pathology",
"biocuration",
"disease",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
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"pipeline_tag": "token-classification",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-DiseaseDetect-ElectraMed-335M](https://huggingface.co/OpenMed/OpenMed-NER-DiseaseDetect-ElectraMed-335M)
**Specialized model for Disease Entity Recognition - Disease entities from the BC5CDR dataset**
[](https://opensource.org/lic... | null | [
"apache-2.0"
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Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source ch... | null | [
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"id": "microsoft/Orca-2-13b"
}
],
"relation": "finetune"
} | 4 | 194,197 | False | 2023-12-13T03:41:38Z | 2023-12-15T15:22:14Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 13015895040}, "total": 13015895040} | [
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Make sure to comply with the mic... | null | [
"other"
] | [
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**Specialized model for Clinical Entity Recognition - Clinical entities related to Chronic Lymphocytic Leukemia**
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# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Usage](#usage)
3. [Uses](#uses)
4. [Bias, Risks, and Limitations](#bias-ri... | null | [
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This model map provides information about a model based on Whisper Large v3 that has been fine-tuned for speech recognition in German. Whisper is a powerful speech recognition platform developed by OpenAI. This model has been specially optimized for processing and recognizing German speech.
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should probably proofread and complete it, then remove this comment. -->
# bert-uncased-keyword-extractor
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased... | null | [
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**Specialized model for Biomedical Entity Recognition - Proteins, DNA, RNA, cell lines, and cell types**
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"base_model:finetune:FacebookAI/roberta-base",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": "roberta-base", "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": "storyseeker", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | # 🔭StorySeeker
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [🔭StorySeeker](https://github.com/maria-antoniak/storyseeker) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4343
- Accuracy: 0.8416
## Citation
If you use our data, codebook... | null | [
"mit"
] | null | null | 124,647,170 | null | [
"accuracy"
] | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6878025f5116015d11b3ceaf | bfe694f64f4a18f5 | daab2a732bab72e2 | 128,001 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Strip",
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 22 | OpenMed/OpenMed-NER-PathologyDetect-SuperClinical-434M | OpenMed | null | 88,894 | 505,026 | False | 2025-07-16T19:49:51Z | 2025-08-05T09:37:15Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"BF16": 434015235}, "total": 434015235} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"model.safetensors",
"openmed_vs_sota_grouped_bars.png",
"special_tokens_map.json",
"spm.model",
"test_results.json",
"tokenizer.json",
"tokenizer_config.json"
] | 460b81ef65107d36df1fd34a4360359c121a09cc | [
"transformers",
"safetensors",
"deberta-v2",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"disease-entity-recognition",
"medical-diagnosis",
"ncbi",
"pathology",
"disease",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DebertaV2ForTokenClassification"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | null | null | [
"apache-2.0"
] | null | [
"en"
] | 434,015,235 | null | null | [
"DebertaV2ForTokenClassification",
"AutoModelForTokenClassification",
"deberta-v2"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
67f1969d47e4d96c18e11caa | f17732d101424a3c | 17f3f83f5cc094be | 201,135 | BPE | 439,802 | false | true | true | true | 1,135 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 727 | chutesai/Llama-4-Scout-17B-16E-Instruct | chutesai | {
"models": [
{
"_id": "67ed6ddf89be3b57ec4eb9be",
"id": "meta-llama/Llama-4-Scout-17B-16E"
}
],
"relation": "finetune"
} | 6 | 192,250 | False | 2025-04-05T20:46:21Z | 2025-04-10T07:22:50Z | transformers | 2 | 0 | null | image-text-to-text | {"parameters": {"BF16": 108641793536}, "total": 108641793536} | [
".gitattributes",
"LICENSE",
"README.md",
"USE_POLICY.md",
"chat_template.json",
"config.json",
"generation_config.json",
"model-00001-of-00050.safetensors",
"model-00002-of-00050.safetensors",
"model-00003-of-00050.safetensors",
"model-00004-of-00050.safetensors",
"model-00005-of-00050.safete... | 1f87ff10c97ec8cc8f493d94f51be43cd2bec2ae | [
"transformers",
"safetensors",
"llama4",
"image-text-to-text",
"facebook",
"meta",
"pytorch",
"llama",
"conversational",
"ar",
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"en",
"es",
"fr",
"hi",
"id",
"it",
"pt",
"th",
"tl",
"vi",
"arxiv:2204.05149",
"base_model:meta-llama/Llama-4-Scout-17B-16E",
"base_mode... | null | {"architectures": ["Llama4ForConditionalGeneration"], "model_type": "llama4", "processor_config": {"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_message = true %}\n{%- en... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["meta-llama/Llama-4-Scout-17B-16E"], "datasets": null, "eval_results": null, "language": ["ar", "de", "en", "es", "fr", "hi", "id", "it", "pt", "th", "tl", "vi"], "library_name": "transformers", "license": "other", "license_name": "llama4", "license_link": null, "metrics": null, "model_name": null, "pip... | null | null | [
"other",
"llama4"
] | null | [
"ar",
"de",
"en",
"es",
"fr",
"hi",
"id",
"it",
"pt",
"th",
"tl",
"vi"
] | 108,641,793,536 | null | null | [
"Llama4ForConditionalGeneration",
"llama4",
"AutoModelForImageTextToText"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
65f3e4953a0b542b87d5a929 | f6bd53b02735a215 | 3f3879d485dc5e16 | 63,992 | BPE | 110,029 | true | false | false | true | 231 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 512 | 01-ai/Yi-9B-200K | 01-ai | null | 8,586 | 239,272 | False | 2024-03-15T06:03:01Z | 2024-11-11T03:31:33Z | transformers | 77 | 0 | null | text-generation | {"parameters": {"BF16": 8829407232}, "total": 8829407232} | [
".gitattributes",
"CHANGELOG.md",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"images/initail.png",
"images/v20240318.png",
"images/v20240321.png",
"md5",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model... | 8efb8b93f2afdd04ec6884352cd0ea727064a95b | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:2403.04652",
"arxiv:2311.16502",
"arxiv:2401.11944",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<|startoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<unk>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "widget": [{"example_title": "Yi-34B-Chat", "text": "hi", "outpu... | - they might want nothing more than destruction itself rather then anything else from their quest after immortality (and maybe someone should tell them about modern medicine)? In any event though – one thing remains true regardless : whether or not success comes easy depends entirely upon how much effort we put into co... | null | [
"apache-2.0"
] | null | null | 8,829,407,232 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63b6e5400d21367c0f61e39a | 2012b52fa41ec860 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 113 | PygmalionAI/pygmalion-2.7b | PygmalionAI | null | 954 | 197,568 | False | 2023-01-05T14:57:04Z | 2023-01-12T19:20:02Z | transformers | 59 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"runs/events.out.tfevents.1672861513.uft-2.228070.0",
"runs/events.out.tfevents.1672879694.uft-2.389061.0",
"runs/events.out.tfevents.1672880794.uft-2.399187.0",
"runs/events.out.tfevents.1672889057.uft-2.472434.0",
"... | 9533805293bc48e8ddfe9dc1940d8cbc5662113e | [
"transformers",
"pytorch",
"tensorboard",
"gpt_neo",
"text-generation",
"text generation",
"conversational",
"en",
"license:creativeml-openrail-m",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPTNeoForCausalLM"], "model_type": "gpt_neo", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "", "lstrip": false, "normalized": true, ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "creativeml-openrail-m", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text generation", "conversational"], "thumbnail": null, "inference":... | # Pygmalion 2.7B
## Model description
Pymalion 2.7B is a proof-of-concept dialogue model based on EleutherAI's [gpt-neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B).
**Warning:** This model is **NOT** suitable for use by minors. It **will** output X-rated content under certain circumstances.
## Training da... | null | [
"creativeml-openrail-m"
] | null | [
"en"
] | null | null | null | [
"gpt_neo",
"AutoModelForCausalLM",
"GPTNeoForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
687a0f9d0b552fa0b3a1d456 | 1f077a9a0005c931 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 230 | OpenMed/OpenMed-NER-BloodCancerDetect-BigMed-278M | OpenMed | null | 88,739 | 506,783 | False | 2025-07-18T09:10:53Z | 2025-08-05T09:46:15Z | transformers | 1 | 0 | null | token-classification | {"parameters": {"BF16": 277455363}, "total": 277455363} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"openmed_vs_sota_grouped_bars.png",
"special_tokens_map.json",
"test_results.json",
"tokenizer.json",
"tokenizer_config.json",
"unigram.json"
] | a104c72de47618eeed6f80424a293c7fc21ccbb6 | [
"transformers",
"safetensors",
"xlm-roberta",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"leukemia",
"hematology",
"cancer",
"clinical-medicine",
"cl",
"en",
"arxiv:2508.01630",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["XLMRobertaForTokenClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["token-classification", "named-entity-recognition", "biomedical-nlp", "transform... | # 🧬 [OpenMed-NER-BloodCancerDetect-BigMed-278M](https://huggingface.co/OpenMed/OpenMed-NER-BloodCancerDetect-BigMed-278M)
**Specialized model for Clinical Entity Recognition - Clinical entities related to Chronic Lymphocytic Leukemia**
[](https://... | null | [
"apache-2.0"
] | null | [
"en"
] | 277,455,363 | null | null | [
"XLMRobertaForTokenClassification",
"AutoModelForTokenClassification",
"xlm-roberta"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
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