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68c971b2d20752b5ed69e748 | baidu/Qianfan-VL-70B | baidu | null | 120 | 1,014 | False | 2025-09-16T14:18:26Z | 2025-09-19T10:32:41Z | transformers | 37 | 1 | null | image-text-to-text | {"parameters": {"BF16": 71839363072}, "total": 71839363072} | [
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68c9bebd89d1fec602dfeaae | ibm-granite/granite-4.0-micro | ibm-granite | null | 108,743 | 378,798 | False | 2025-09-16T19:47:09Z | 2025-11-03T19:39:06Z | transformers | 263 | 1 | null | text-generation | null | [
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68c9bf99092db2992e25c381 | ibm-granite/granite-4.0-h-small | ibm-granite | null | 100,375 | 296,788 | False | 2025-09-16T19:50:49Z | 2025-11-03T19:45:37Z | transformers | 304 | 1 | null | text-generation | null | [
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"conversational",
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] | null | {"architectures": ["GraniteMoeHybridForCausalLM"], "model_type": "granitemoehybrid", "tokenizer_config": {"bos_token": "<|end_of_text|>", "eos_token": "<|end_of_text|>", "pad_token": "<|pad|>", "unk_token": "<|unk|>"}, "chat_template_jinja": "{%- set tools_system_message_prefix = 'You are a helpful assistant with acces... | {
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"apache-2.0"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
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68c9bfb45f6dca45c103b900 | ibm-granite/granite-4.0-h-tiny | ibm-granite | null | 42,299 | 170,255 | False | 2025-09-16T19:51:16Z | 2025-11-03T19:42:57Z | transformers | 197 | 1 | null | text-generation | {"parameters": {"BF16": 6939037248}, "total": 6939037248} | [
".gitattributes",
"README.md",
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"to... | 791e0d3d28c86e106c9b6e0b4cecdee0375b6124 | [
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"conversational",
"arxiv:0000.00000",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
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] | null | {"architectures": ["GraniteMoeHybridForCausalLM"], "model_type": "granitemoehybrid", "tokenizer_config": {"bos_token": "<|end_of_text|>", "eos_token": "<|end_of_text|>", "pad_token": "<|pad|>", "unk_token": "<|unk|>"}, "chat_template_jinja": "{%- set tools_system_message_prefix = 'You are a helpful assistant with acces... | {
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"apache-2.0"
] | null | null | 6,939,037,248 | null | null | [
"AutoModelForCausalLM",
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68c9c0c0fc3e0118046b2166 | ibm-granite/granite-4.0-micro-base | ibm-granite | null | 132,082 | 145,692 | False | 2025-09-16T19:55:44Z | 2025-11-03T19:40:17Z | transformers | 40 | 1 | null | text-generation | {"parameters": {"BF16": 3402836480}, "total": 3402836480} | [
".gitattributes",
"README.md",
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"model.sig",
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] | 98e1d641451818f6c8e6b17c1c359b5b4ac495d0 | [
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"text-generation",
"language",
"granite-4.0",
"license:apache-2.0",
"endpoints_compatible",
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] | null | {"architectures": ["GraniteMoeHybridForCausalLM"], "model_type": "granitemoehybrid", "tokenizer_config": {"bos_token": "<|end_of_text|>", "eos_token": "<|end_of_text|>", "pad_token": "<|pad|>", "unk_token": "<|unk|>"}} | {
"auto_model": "AutoModelForCausalLM",
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"apache-2.0"
] | null | null | 3,402,836,480 | null | null | [
"AutoModelForCausalLM",
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68ccce570346a053ed14ab78 | TencentARC/ARC-Qwen-Video-7B-Narrator | TencentARC | {
"models": [
{
"_id": "6795ffcd88cd7c0294702a72",
"id": "Qwen/Qwen2.5-VL-7B-Instruct"
}
],
"relation": "finetune"
} | 55 | 409 | False | 2025-09-19T03:30:31Z | 2025-09-21T14:24:13Z | transformers | 11 | 1 | null | video-text-to-text | {"parameters": {"BF16": 8946577920}, "total": 8946577920} | [
".gitattributes",
"README.md",
"added_tokens.json",
"args.json",
"chat_template.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model... | 1b14d12fac795617d51cd972496c08d0a1d44133 | [
"transformers",
"safetensors",
"multimodal",
"video-understanding",
"video-audio understanding",
"video-captioning",
"video-reasoning",
"short video understanding",
"video-text-to-text",
"arxiv:2507.20939",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instr... | null | null | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": ["Qwen/Qwen2.5-VL-7B-Instruct"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "video-text-to-text", "tags": ["multimodal", "video-understa... | # ARC-Qwen-Video-7B
[](https://arxiv.org/abs/2507.20939)
[](https://arc.tencent.com/en/ai-demos/multimodal)
[](https://github.com/TencentARC/ARC-H... | null | [
"apache-2.0"
] | null | null | 8,946,577,920 | null | null | [
"AutoModel"
] | [
null,
"video-text-to-text"
] | [
"vision"
] | [
"text",
"image"
] | [
"text"
] |
68d185fcf44273da274ab279 | LiquidAI/LFM2-2.6B | LiquidAI | null | 8,382 | 271,836 | False | 2025-09-22T17:23:08Z | 2026-02-12T17:33:04Z | transformers | 182 | 1 | null | text-generation | {"parameters": {"BF16": 2569272320}, "total": 2569272320} | [
".gitattributes",
"LICENSE",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | e161ff2aa73314dc0b45b1d461bb99630ef8ebc6 | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"liquid",
"edge",
"conversational",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"arxiv:2511.23404",
"license:other",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Lfm2ForCausalLM"], "model_type": "lfm2", "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|im_end|>", "pad_token": "<|pad|>", "use_default_system_prompt": false}, "chat_template_jinja": "{{- bos_token -}}{%- set system_prompt = \"\" -%}{%- set ns = namespace(system_prompt=\"\") -%... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "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", "tags": ["liquid", "... | <center>
<div style="text-align: center;">
<img
src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/7_6D7rWrLxp2hb6OHSV1p.png"
alt="Liquid AI"
style="width: 100%; max-width: 66%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
/>
</div>
<d... | null | [
"other",
"lfm1.0",
"LICENSE"
] | null | [
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es"
] | 2,569,272,320 | null | null | [
"Lfm2ForCausalLM",
"AutoModelForCausalLM",
"lfm2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68d285f548f18aa202a8c019 | Qwen/Qwen3Guard-Gen-0.6B | Qwen | {
"models": [
{
"_id": "680da718233834890aa01f51",
"id": "Qwen/Qwen3-0.6B"
}
],
"relation": "finetune"
} | 213,944 | 756,607 | False | 2025-09-23T11:35:17Z | 2025-11-07T08:10:53Z | transformers | 64 | 1 | null | text-generation | {"parameters": {"BF16": 751632384}, "total": 751632384} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | fada3b2f655b89601929198343c94cd2f64d93cc | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"arxiv:2510.14276",
"base_model:Qwen/Qwen3-0.6B",
"base_model:finetune:Qwen/Qwen3-0.6B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if messages|length > 0 -%}\n {%- if messages[-1].role == \"user\" -%}\n {{- \"<|im_start|>user\n# Task:\n1) Evaluate whether THE LAST USER's query belongs to safe or unsafe content base... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen3-0.6B"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3Guard-Gen-0.6B/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-gen... | # Qwen3Guard-Gen-0.6B
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3Guard/Qwen3Guard_logo.png" width="400"/>
<p>
**Qwen3Guard** is a series of safety moderation models built upon Qwen3 and trained on a dataset of 1.19 million prompts and responses labeled for safety. The series... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3Guard-Gen-0.6B/blob/main/LICENSE"
] | null | null | 751,632,384 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68d28a121a3492f8a2b4eeb1 | Qwen/Qwen3Guard-Stream-8B | Qwen | {
"models": [
{
"_id": "680da79d48c19d19cf82ab5e",
"id": "Qwen/Qwen3-8B"
}
],
"relation": "finetune"
} | 420 | 8,184 | False | 2025-09-23T11:52:50Z | 2025-11-07T07:35:13Z | transformers | 34 | 1 | null | feature-extraction | {"parameters": {"BF16": 7572612608}, "total": 7572612608} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"configuration_qwen3.py",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.js... | f14fba01154127167c77c0e9f80536cec56e7b69 | [
"transformers",
"safetensors",
"qwen3",
"feature-extraction",
"custom_code",
"arxiv:2510.14276",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen3ForGuardModel"], "auto_map": {"AutoConfig": "configuration_qwen3.Qwen3Config", "AutoModel": "modeling_qwen3_guard.Qwen3ForGuardModel"}, "model_type": "qwen3", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].ro... | {
"auto_model": "AutoModel",
"custom_class": "modeling_qwen3_guard.Qwen3ForGuardModel",
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen3-8B"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3Guard-Stream-8B/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tag... | # Qwen3Guard-Stream-8B
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3Guard/Qwen3Guard_logo.png" width="400"/>
<p>
**Qwen3Guard** is a series of safety moderation models built upon Qwen3 and trained on a dataset of 1.19 million prompts and responses labeled for safety. The serie... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3Guard-Stream-8B/blob/main/LICENSE"
] | null | null | 7,572,612,608 | null | null | [
"modeling_qwen3_guard.Qwen3ForGuardModel",
"AutoModel",
"Qwen3ForGuardModel",
"qwen3"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
68d33e16f256c81fdcf133b5 | ServiceNow-AI/Apriel-1.5-15b-Thinker | ServiceNow-AI | null | 325 | 69,806 | False | 2025-09-24T00:40:54Z | 2025-10-06T18:55:51Z | transformers | 467 | 1 | null | image-text-to-text | null | [
".gitattributes",
"Apriel-1.5-Thinker.pdf",
"README.md",
"chat_template.json",
"config.json",
"generation_config.json",
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"model-00002-of-00007.safetensors",
"model-00003-of-00007.safetensors",
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68d4576e9ca51820a41edf14 | kiethuynhanh/llama-3.2-vision-docvqa | kiethuynhanh | {
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- **Developed by:** kiethuynhanh
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Llama-3.2-11B-Vision-Instruct-unsloth-bnb-4bit
This mllama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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68d5abebaa74b0f261514346 | Snqwii/mag-pe-dt | Snqwii | {
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68d62d9d9abc92c5d6b4e3ed | Kwaipilot/HiPO-8B | Kwaipilot | {
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],
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} | 9 | 968 | False | 2025-09-26T06:07:25Z | 2025-11-04T02:37:23Z | transformers | 23 | 1 | null | text-generation | {"parameters": {"BF16": 8190735360}, "total": 8190735360} | [
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68d7f074837b83cd932db596 | huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated-v2 | huihui-ai | {
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} | 7,923 | 36,675 | False | 2025-09-27T14:11:00Z | 2025-09-28T07:44:57Z | transformers | 38 | 1 | null | text-generation | {"parameters": {"BF16": 20914757184}, "total": 20914757184} | [
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68d8cf481fcde33127b11c01 | OpenGVLab/InternVL3_5-8B-Flash | OpenGVLab | {
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} | 265 | 83,603 | False | 2025-09-28T06:01:44Z | 2025-09-28T06:43:05Z | transformers | 5 | 1 | null | image-text-to-text | {"parameters": {"BF16": 8813642754}, "total": 8813642754} | [
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68d9a1cdf0a667ce385c567c | amd/Phi-3-mini-4k-instruct-onnx-ryzenai-npu | amd | {
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} | 15 | 184 | False | 2025-09-28T20:59:57Z | 2025-10-23T20:33:42Z | transformers | 1 | 1 | null | text-generation | null | [
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68da95c801cfcc35dfadbd06 | cyankiwi/Qwen3-Omni-30B-A3B-Instruct-AWQ-8bit | cyankiwi | {
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} | 938 | 11,606 | False | 2025-09-29T14:20:56Z | 2025-09-29T14:40:40Z | transformers | 6 | 1 | null | any-to-any | {"parameters": {"F16": 6297100849, "I64": 37248, "I32": 7474249728}, "total": 13771387825} | [
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68daa34ef2199ef1ecbaf343 | moonstruxx/MinerU2.5-2509-1.2B-mlx-fp16 | moonstruxx | {
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} | 70 | 445 | False | 2025-09-29T15:18:38Z | 2025-09-29T15:18:51Z | transformers | 2 | 1 | null | image-text-to-text | {"parameters": {"F16": 494032768}, "total": 494032768} | [
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68dace7bccfdaf8c81d0243d | zai-org/GLM-4.6 | zai-org | null | 22,471 | 651,590 | False | 2025-09-29T18:22:51Z | 2025-09-30T10:17:45Z | transformers | 1,207 | 1 | null | text-generation | {"parameters": {"BF16": 356785884416, "F32": 14400}, "total": 356785898816} | [
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68dbb0130bcd1813a6e95d91 | Qwen/Qwen3-4B-SafeRL | Qwen | {
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68dbe25aa86e478f543e8dc0 | nvidia/omni-embed-nemotron-3b | nvidia | null | 2,499 | 50,652 | False | 2025-09-30T13:59:54Z | 2025-10-09T23:07:04Z | transformers | 98 | 1 | null | feature-extraction | {"parameters": {"BF16": 4703464448}, "total": 4703464448} | [
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68df52181da0a5d78f4d9b23 | DreadPoor/Famino-12B-Model_Stock | DreadPoor | {
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68e426671e0b9788f78c2a8c | cisco-ai/SecureBERT2.0-code-vuln-detection | cisco-ai | {
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68e43cc4a98fb480f4d9d5b0 | allenai/olmOCR-2-7B-1025-FP8 | allenai | {
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68e576fb3bef55c798481b7f | ibm-granite/granite-4.0-1b | ibm-granite | {
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68e902b0cddede4ab0d32dc1 | Open-Bee/Bee-8B-RL | Open-Bee | {
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68ea4a12e79b11c58973069b | ljw13/retro-star-qwen3-32b-0928 | ljw13 | {
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68ea8d6315ff98c4d4233929 | KORMo-Team/KORMo-10B-base | KORMo-Team | null | 86 | 6,680 | False | 2025-10-11T17:01:23Z | 2026-03-18T18:54:11Z | transformers | 38 | 1 | null | text-generation | {"parameters": {"BF16": 10756624384}, "total": 10756624384} | [
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68ecec88b845b2eff791db77 | nanonets/Nanonets-OCR2-3B | nanonets | {
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68edfbbf838ec1838b2b37af | ethicalabs/xLSTM-7b-Instruct | ethicalabs | {
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68ef49eb041caf03c1ef1b89 | prithivMLmods/Qwen3-VL-4B-Thinking-abliterated-v1 | prithivMLmods | {
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68ef6a5157f4f4414ddc1478 | thelamapi/next-4b | thelamapi | null | 186 | 3,297 | False | 2025-10-15T09:33:05Z | 2026-03-01T18:16:44Z | transformers | 7 | 1 | null | image-text-to-text | {"parameters": {"BF16": 4300079472}, "total": 4300079472} | [
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68f0e462587c5183dc6c0a59 | huihui-ai/Huihui-Qwen3-VL-8B-Thinking-abliterated | huihui-ai | {
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68f209329e541148eac9a713 | RUC-DataLab/DeepAnalyze-8B | RUC-DataLab | null | 8,273 | 21,429 | False | 2025-10-17T09:15:30Z | 2025-10-26T08:09:27Z | transformers | 86 | 1 | null | text-generation | {"parameters": {"BF16": 8190735360}, "total": 8190735360} | [
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68f2a0fd654717c2b0b858d5 | ghananlpcommunity/opani-coder_1b-merged-16bit | ghananlpcommunity | {
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68f3a958da5c6360d882d4eb | lapa-llm/lapa-v0.1.2-instruct | lapa-llm | {
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} | 2,365 | 8,485 | False | 2025-10-18T14:51:04Z | 2025-11-02T23:44:22Z | transformers | 23 | 1 | null | image-text-to-text | {"parameters": {"BF16": 12187325040}, "total": 12187325040} | [
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68f657d300f6d911ff2482f5 | cerebras/Qwen3-Coder-REAP-25B-A3B | cerebras | {
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68f658c671030d6ea663fc32 | cerebras/GLM-4.5-Air-REAP-82B-A12B | cerebras | {
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68f8b9ddf59c97a3ec9eaa68 | huihui-ai/Huihui-Qwen3-VL-2B-Instruct-abliterated | huihui-ai | {
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} | 630 | 11,261 | False | 2025-10-22T11:02:53Z | 2025-12-15T07:32:56Z | transformers | 17 | 1 | null | image-text-to-text | {"parameters": {"BF16": 2127532032}, "total": 2127532032} | [
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68f9f880858797baaba8321d | meituan-longcat/LongCat-Flash-Omni | meituan-longcat | null | 90 | 950 | False | 2025-10-23T09:42:24Z | 2025-11-11T02:50:56Z | transformers | 109 | 1 | null | any-to-any | {"parameters": {"BF16": 560532838400, "F32": 132142080}, "total": 560664980480} | [
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68fb09e0b0ae6b04409d2631 | Alibaba-NLP/E2Rank-8B | Alibaba-NLP | {
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68fdb085a07eb927368eb17c | DarkNeuronAI/darkneuron-chat-v1.1 | DarkNeuronAI | {
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68fe3d0d5418164b902a2058 | kenpath/svara-tts-v1 | kenpath | {
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69002272be871d88210882a2 | podsni/hades-1B | podsni | {
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6900b7e7bf9e52eb807f6133 | OpenMOSS-Team/RoboOmni-LIBERO-Spatial | OpenMOSS-Team | {
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} | 12 | 129 | False | 2025-10-28T12:32:39Z | 2025-10-31T12:34:12Z | transformers | 3 | 1 | null | robotics | null | [
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69014050c487462c09002b2d | ByteDance/Ouro-1.4B-Thinking | ByteDance | null | 3,692 | 14,992 | False | 2025-10-28T22:14:40Z | 2026-02-26T18:40:10Z | transformers | 32 | 1 | null | text-generation | null | [
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69033bc029f07636a92d6c62 | truptimohanty/CrysText-RL | truptimohanty | {
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69045311eb7b630406985187 | Nanbeige/Nanbeige4-3B-Base | Nanbeige | null | 3,600 | 7,727 | False | 2025-10-31T06:11:29Z | 2025-12-13T06:18:03Z | transformers | 60 | 1 | null | text-generation | {"parameters": {"BF16": 3933637120}, "total": 3933637120} | [
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69047d1b114ec710fed502df | Alibaba-NLP/GVE-3B | Alibaba-NLP | {
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} | 704 | 1,808 | False | 2025-10-31T09:10:51Z | 2025-11-03T08:30:18Z | transformers | 17 | 1 | null | sentence-similarity | {"parameters": {"BF16": 3754622976}, "total": 3754622976} | [
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69052d6985088539824d2bed | salakash/SamKash-Tolstoy | salakash | {
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67f5d4102af5e0118b57de5d | VIDraft/Gemma-3-R1984-4B | VIDraft | {
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} | 8 | 8,180 | False | 2025-04-09T01:57:36Z | 2025-04-10T02:17:06Z | transformers | 21 | 0.5 | null | image-text-to-text | {"parameters": {"BF16": 4300079472}, "total": 4300079472} | [
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# Model Overview
Gemma3-R1984-4B is a robust Agentic AI platform built on Googls’s Gemma-3-4B model. It integrates state-of-the-art deep research via web search with multimodal file processing—including images, videos, and documents—and handles long contexts up to 8,000 tokens. Designed for local dep... | null | [
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68860e286963bab90abae270 | HelpingAI/Dhanishtha-nsfw | HelpingAI | {
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65571ab5bff42e6fa5c7a9d0 | voxta/MLewd-L2-Chat-13B-3.3bpw-exl2 | voxta | null | 5 | 291 | False | 2023-11-17T07:48:05Z | 2023-11-17T07:55:20Z | transformers | 4 | 0.1 | null | text-generation | null | [
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65ce2e194396608345797077 | TeeZee/DarkForest-20B-v2.0 | TeeZee | null | 160 | 12,961 | False | 2024-02-15T15:30:33Z | 2024-06-13T11:32:26Z | transformers | 42 | 0.1 | [{"name": "DarkForest-20B-v2.0", "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": 63.74, "name": "n... | text-generation | {"parameters": {"BF16": 19994362880}, "total": 19994362880} | [
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6679cb2726fccf94e2d128be | Casual-Autopsy/L3-Uncen-Merger-Omelette-RP-v0.1.1-8B | Casual-Autopsy | {
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6700687590e1fe6f74d82ac7 | Vikhrmodels/Vikhr-Llama-3.2-1B-Instruct-abliterated | Vikhrmodels | {
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67955d1bc16b74e280ff1ccd | mergekit-community/Deepseek-R1-Distill-NSFW-RPv1 | mergekit-community | {
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67f53cc0baa27cc9b64952e9 | Delta-Vector/Pascal-12B | Delta-Vector | {
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681e3a39f4fd0018cb9a9e0c | Novaciano/SEX_RP_V2-3.2-1B | Novaciano | {
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68225a662292930019d24b69 | Casual-Autopsy/The-True-Abomination-24B | Casual-Autopsy | {
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] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "eos_token": "<|eot_id|>", "pad_token": "<|finetune_right_pad_id|>"}, "chat_template_jinja": "{% set loop_messages = messages %}\n{% for message in loop_messages %}\n{% set content = '<|start_header_id|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": [], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["mergekit", "merge", "unaligned", "not-for-all-audiences"]} | null | null | null | null | null | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68cc211ebde2d20b06fa94a6 | Mawdistical/Mawnia-12B | Mawdistical | {
"models": [
{
"_id": "67df9d8fc6f5a09be26c2539",
"id": "allura-org/Gemma-3-Glitter-12B"
}
],
"relation": "finetune"
} | 4 | 244 | False | 2025-09-18T15:11:26Z | 2025-09-20T05:59:08Z | transformers | 6 | 0.1 | null | text-generation | {"parameters": {"BF16": 12187325040}, "total": 12187325040} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
... | 4d1ea8e8890a792657d9b31bf3f1250ca5d64557 | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"nsfw",
"explicit",
"roleplay",
"mixed-AI",
"furry",
"anthro",
"dark",
"chat",
"text-generation",
"conversational",
"en",
"base_model:allura-org/Gemma-3-Glitter-12B",
"base_model:finetune:allura-org/Gemma-3-Glitter-12B",
... | null | {"architectures": ["Gemma3ForConditionalGeneration"], "model_type": "gemma3", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<end_of_turn>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}, "chat_template_jinja": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n ... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["allura-org/Gemma-3-Glitter-12B"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["nsfw", "explicit", "roleplay", ... | null | null | [
"other"
] | null | [
"en"
] | 12,187,325,040 | null | null | [
"AutoModelForImageTextToText",
"Gemma3ForConditionalGeneration",
"gemma3"
] | [
"image-text-to-text",
"text-generation"
] | [
"text",
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
68ea6907290643a279cd39f4 | gggrandma1990/L3-8B-Wingless-Moon-Maiden | gggrandma1990 | {
"models": [
{
"_id": "66a1784708767ced9f41134a",
"id": "NeverSleep/Lumimaid-v0.2-8B"
},
{
"_id": "667b636c8c44b132c0e75ca7",
"id": "Sao10K/L3-8B-Lunaris-v1"
},
{
"_id": "67936012e78e2f061d4b0dfe",
"id": "SicariusSicariiStuff/Wingless_Imp_8B"
}
],
"rela... | 13 | 135 | False | 2025-10-11T14:26:15Z | 2025-10-11T21:16:25Z | transformers | 6 | 0.1 | null | text-generation | {"parameters": {"BF16": 8030285824}, "total": 8030285824} | [
".gitattributes",
"README.md",
"config.json",
"config.yml",
"imatrix.dat",
"mergekit_config.yml",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_tokens_map.... | d04c33bde478af71da520bbfdfa51706b6ae9923 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"merge",
"not-for-all-audiences",
"conversational",
"arxiv:2406.11617",
"base_model:NeverSleep/Lumimaid-v0.2-8B",
"base_model:merge:NeverSleep/Lumimaid-v0.2-8B",
"base_model:Sao10K/L3-8B-Lunaris-v1",
"base_model:merge:Sao10K/L3-8B-Luna... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}\n{% for message in loop_messages %}\n{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["NeverSleep/Lumimaid-v0.2-8B", "Sao10K/L3-8B-Lunaris-v1", "SicariusSicariiStuff/Wingless_Imp_8B"], "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": n... | null | null | null | null | null | 8,030,285,824 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174328 | albert/albert-base-v1 | albert | null | 135,447 | 3,734,672 | False | 2022-03-02T23:29:04Z | 2024-02-19T10:57:35Z | transformers | 12 | 0 | null | fill-mask | {"parameters": {"F32": 11842272}, "total": 11842272} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | 082438ba120d36b97b9288772a41144e941705b9 | [
"transformers",
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["exbert"]} | # ALBERT Base v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make ... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 11,842,272 | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174329 | albert/albert-base-v2 | albert | null | 629,246 | 161,471,707 | False | 2022-03-02T23:29:04Z | 2024-02-19T10:58:14Z | transformers | 140 | 0 | null | fill-mask | {"parameters": {"F32": 11842272}, "total": 11842272} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"rust_model.ot",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | 8e2f239c5f8a2c0f253781ca60135db913e5c80c | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT Base v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make ... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 11,842,272 | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17432a | albert/albert-large-v1 | albert | null | 713 | 171,244 | False | 2022-03-02T23:29:04Z | 2024-02-19T10:58:26Z | transformers | 3 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | 94fd741fb5d6cb5bc578fc154837016c583bafef | [
"transformers",
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT Large v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | null | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17432b | albert/albert-large-v2 | albert | null | 2,954 | 2,696,751 | False | 2022-03-02T23:29:04Z | 2024-02-19T10:58:48Z | transformers | 21 | 0 | null | fill-mask | {"parameters": {"F32": 17875424}, "total": 17875424} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | dfed3a5ef4499fb3351c4ebbcf487375d1e942c8 | [
"transformers",
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT Large v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 17,875,424 | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17432c | albert/albert-xlarge-v1 | albert | null | 690 | 273,677 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:01:28Z | transformers | 4 | 0 | null | fill-mask | {"parameters": {"F32": 59047392}, "total": 59047392} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | ed6f87d14403b3c459a458fa6aa9dc5c51c517c1 | [
"transformers",
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT XLarge v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not mak... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 59,047,392 | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17432d | albert/albert-xlarge-v2 | albert | null | 1,130 | 474,035 | False | 2022-03-02T23:29:04Z | 2024-04-10T09:57:46Z | transformers | 13 | 0 | null | fill-mask | {"parameters": {"F32": 59047392}, "total": 59047392} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | 4fd2c2aa9aeb305f87704a7e595be7bfffa3db88 | [
"transformers",
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT XLarge v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not mak... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 59,047,392 | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17432e | albert/albert-xxlarge-v1 | albert | null | 751 | 403,015 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:01:42Z | transformers | 5 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | 43129068ee5f6a481c148daeac11cc593b8ff440 | [
"transformers",
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT XXLarge v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not ma... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | null | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17432f | albert/albert-xxlarge-v2 | albert | null | 2,681 | 2,036,251 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:02:09Z | transformers | 21 | 0 | null | fill-mask | {"parameters": {"F32": 223180256}, "total": 223180256} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"rust_model.ot",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"with-prefix-tf_model.h5"
] | 97d3e58863d3a41dc581882f73b34d110b18f1f8 | [
"transformers",
"pytorch",
"tf",
"rust",
"safetensors",
"albert",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "model_type": "albert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["exbert"]} | # ALBERT XXLarge v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not ma... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 223,180,256 | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174330 | google-bert/bert-base-cased-finetuned-mrpc | google-bert | null | 29,574 | 1,562,573 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:03:21Z | transformers | 3 | 0 | null | fill-mask | {"parameters": {"F32": 108311810}, "total": 108311810} | [
".gitattributes",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | f150c1d609d1e50dd5e2e5408661cfac8339277c | [
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"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | 108,311,810 | null | null | [
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"bert",
"BertForMaskedLM"
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621ffdc036468d709f174333 | google-bert/bert-base-german-cased | google-bert | null | 464,276 | 15,322,556 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:03:41Z | transformers | 82 | 0 | null | fill-mask | {"parameters": {"F32": 109705010}, "total": 109705010} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"onnx/added_tokens.json",
"onnx/config.json",
"onnx/generation_config.json",
"onnx/model.onnx",
"onnx/special_tokens_map.json",
"onnx/tokenizer.json",
"onnx/tokenizer_config.json",
"onnx/vocab.txt",
"p... | 0b061b4f7ce140d10dce6b6bd8a77da8ec80931b | [
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"bert",
"fill-mask",
"exbert",
"de",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "de", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["exbert"], "thumbnail": "https://static.tildacdn.com/tild6438-3730-4164-b266-613634323466... | <a href="https://huggingface.co/exbert/?model=bert-base-german-cased">
<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
</a>
# German BERT
## Overview
**Language model:** bert-base-cased
**La... | null | [
"mit"
] | null | [
"de"
] | 109,705,010 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
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"fill-mask"
] | [
"text"
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"text"
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"logits"
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621ffdc036468d709f174334 | google-bert/bert-base-german-dbmdz-cased | google-bert | null | 77 | 3,106,560 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:03:54Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | f14984d5ec25548212323f69adc0f39dd47336ea | [
"transformers",
"pytorch",
"jax",
"bert",
"fill-mask",
"de",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "de", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | This model is the same as [dbmdz/bert-base-german-cased](https://huggingface.co/dbmdz/bert-base-german-cased). See the [dbmdz/bert-base-german-cased model card](https://huggingface.co/dbmdz/bert-base-german-cased) for details on the model. | null | [
"mit"
] | null | [
"de"
] | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
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"text"
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"logits"
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621ffdc036468d709f174335 | google-bert/bert-base-german-dbmdz-uncased | google-bert | null | 10,952 | 3,488,478 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:05:32Z | transformers | 4 | 0 | null | fill-mask | {"parameters": {"F32": 110552448}, "total": 110552448} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 0c4f9b72974a493dea3dc4ea23ea1c4c22ff7732 | [
"transformers",
"pytorch",
"jax",
"safetensors",
"bert",
"fill-mask",
"de",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "de", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | This model is the same as [dbmdz/bert-base-german-uncased](https://huggingface.co/dbmdz/bert-base-german-uncased). See the [dbmdz/bert-base-german-cased model card](https://huggingface.co/dbmdz/bert-base-german-uncased) for details on the model. | null | [
"mit"
] | null | [
"de"
] | 110,552,448 | null | null | [
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"bert",
"BertForMaskedLM"
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"fill-mask"
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"text"
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"text"
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"logits"
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621ffdc036468d709f174336 | google-bert/bert-base-multilingual-cased | google-bert | null | 3,717,654 | 242,245,368 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:05:41Z | transformers | 580 | 0 | null | fill-mask | {"parameters": {"F32": 178566653}, "total": 178566653} | [
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"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 3f076fdb1ab68d5b2880cb87a0886f315b8146f8 | [
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"tf",
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"af",
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"ceb",
"ce",
"zh",
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"nl"... | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
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} | {"base_model": null, "datasets": ["wikipedia"], "eval_results": null, "language": ["multilingual", "af", "sq", "ar", "an", "hy", "ast", "az", "ba", "eu", "bar", "be", "bn", "inc", "bs", "br", "bg", "my", "ca", "ceb", "ce", "zh", "cv", "hr", "cs", "da", "nl", "en", "et", "fi", "fr", "gl", "ka", "de", "el", "gu", "ht", "... | # BERT multilingual base model (cased)
Pretrained model on the top 104 languages with the largest Wikipedia using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model ... | null | [
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... | 178,566,653 | null | null | [
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621ffdc036468d709f174337 | google-bert/bert-base-multilingual-uncased | google-bert | null | 5,029,569 | 95,498,149 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:06:00Z | transformers | 153 | 0 | null | fill-mask | null | [
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Pretrained model on the top 102 languages with the largest Wikipedia using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This mode... | null | [
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... | null | null | null | [
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621ffdc036468d709f174339 | google-bert/bert-large-cased-whole-word-masking-finetuned-squad | google-bert | null | 40,735 | 2,157,682 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:06:38Z | transformers | 1 | 0 | null | question-answering | {"parameters": {"F32": 333581314}, "total": 333581314} | [
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Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is cas... | null | [
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621ffdc036468d709f17433a | google-bert/bert-large-cased-whole-word-masking | google-bert | null | 498 | 401,133 | False | 2022-03-02T23:29:04Z | 2024-04-10T09:56:46Z | transformers | 23 | 0 | null | fill-mask | {"parameters": {"F32": 334661958}, "total": 334661958} | [
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Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is cased: it makes a diff... | null | [
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621ffdc036468d709f17433b | google-bert/bert-large-cased | google-bert | null | 64,749 | 20,999,716 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:06:20Z | transformers | 36 | 0 | null | fill-mask | {"parameters": {"F32": 334661958}, "total": 334661958} | [
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"auto_model": "AutoModelForMaskedLM",
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Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is cased: it makes a difference
between engl... | null | [
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621ffdc036468d709f17433c | google-bert/bert-large-uncased-whole-word-masking-finetuned-squad | google-bert | null | 138,941 | 36,750,206 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:08:45Z | transformers | 188 | 0 | null | question-answering | {"parameters": {"F32": 335143938}, "total": 335143938} | [
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"auto_model": "AutoModelForQuestionAnswering",
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Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is u... | null | [
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621ffdc036468d709f17433d | google-bert/bert-large-uncased-whole-word-masking | google-bert | null | 7,624 | 3,167,220 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:08:36Z | transformers | 22 | 0 | null | fill-mask | {"parameters": {"F32": 336226108}, "total": 336226108} | [
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Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is uncased: it does not... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 336,226,108 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17433e | google-bert/bert-large-uncased | google-bert | null | 350,123 | 85,997,164 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:06:54Z | transformers | 146 | 0 | null | fill-mask | {"parameters": {"F32": 336226108}, "total": 336226108} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"model.safetensors",
"pytorch_model.bin",
"rust_model.ot",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt",
"whole-word-masking.tar.gz"
] | 6da4b6a26a1877e173fca3225479512db81a5e5b | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # BERT large model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is uncased: it does not make a difference
... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 336,226,108 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17433f | almanach/camembert-base | almanach | null | 877,691 | 92,204,561 | False | 2022-03-02T23:29:04Z | 2025-06-23T14:02:30Z | transformers | 99 | 0 | null | fill-mask | {"parameters": {"F32": 111246085}, "total": 111246085} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json"
] | a75967561c78f2aa81cc41045378d3b4ee25af9e | [
"transformers",
"pytorch",
"tf",
"safetensors",
"camembert",
"fill-mask",
"fr",
"dataset:oscar",
"arxiv:1911.03894",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["CamembertForMaskedLM"], "model_type": "camembert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["oscar"], "eval_results": null, "language": "fr", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # CamemBERT: a Tasty French Language Model
## Introduction
[CamemBERT](https://arxiv.org/abs/1911.03894) is a state-of-the-art language model for French based on the RoBERTa model.
It is now available on Hugging Face in 6 different versions with varying number of parameters, amount of pretraining data and pretraini... | null | [
"mit"
] | [
"oscar"
] | [
"fr"
] | 111,246,085 | null | null | [
"CamembertForMaskedLM",
"AutoModelForMaskedLM",
"camembert"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174342 | distilbert/distilbert-base-cased | distilbert | null | 171,977 | 30,776,155 | False | 2022-03-02T23:29:04Z | 2024-05-06T13:46:22Z | transformers | 60 | 0 | null | fill-mask | {"parameters": {"F32": 65812036}, "total": 65812036} | [
".gitattributes",
"README.md",
"config.json",
"model.onnx",
"model.safetensors",
"pytorch_model.bin",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6ea81172465e8b0ad3fddeed32b986cdcdcffcf0 | [
"transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"distilbert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1910.01108",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertForMaskedLM"], "model_type": "distilbert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Model Card for DistilBERT base model (cased)
This model is a distilled version of the [BERT base model](https://huggingface.co/bert-base-cased).
It was introduced in [this paper](https://arxiv.org/abs/1910.01108).
The code for the distillation process can be found
[here](https://github.com/huggingface/transformers/t... | null | [
"apache-2.0"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 65,812,036 | null | null | [
"distilbert",
"AutoModelForMaskedLM",
"DistilBertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174343 | distilbert/distilbert-base-german-cased | distilbert | null | 275,900 | 4,175,308 | False | 2022-03-02T23:29:04Z | 2024-05-06T13:46:46Z | transformers | 25 | 0 | null | fill-mask | {"parameters": {"F32": 67431550}, "total": 67431550} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6f96562de9886779ce7d48810dff8f5c4afb6d0b | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"fill-mask",
"de",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertForMaskedLM"], "model_type": "distilbert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "de", "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 | [
"de"
] | 67,431,550 | null | null | [
"distilbert",
"AutoModelForMaskedLM",
"DistilBertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174344 | distilbert/distilbert-base-multilingual-cased | distilbert | null | 892,115 | 114,385,244 | False | 2022-03-02T23:29:04Z | 2024-05-06T13:46:54Z | transformers | 236 | 0 | null | fill-mask | {"parameters": {"F32": 135445755}, "total": 135445755} | [
".gitattributes",
"README.md",
"config.json",
"model.onnx",
"model.safetensors",
"pytorch_model.bin",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 45c032ab32cc946ad88a166f7cb282f58c753c2e | [
"transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"distilbert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",... | null | {"architectures": ["DistilBertForMaskedLM"], "model_type": "distilbert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["wikipedia"], "eval_results": null, "language": ["multilingual", "af", "sq", "ar", "an", "hy", "ast", "az", "ba", "eu", "bar", "be", "bn", "inc", "bs", "br", "bg", "my", "ca", "ceb", "ce", "zh", "cv", "hr", "cs", "da", "nl", "en", "et", "fi", "fr", "gl", "ka", "de", "el", "gu", "ht", "... | # Model Card for DistilBERT base multilingual (cased)
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training Details](#training-details)
5. [Evaluation](#evaluation)
6. [Environmental Impact](#environmental-impact)
7. [Citati... | null | [
"apache-2.0"
] | [
"wikipedia"
] | [
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl",
"en",
"et",
"fi",
"fr",
"gl",
"ka",
"de",
"el",
"gu",
"ht",
"he",
... | 135,445,755 | null | null | [
"distilbert",
"AutoModelForMaskedLM",
"DistilBertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174345 | distilbert/distilbert-base-uncased-distilled-squad | distilbert | null | 45,817 | 12,925,416 | False | 2022-03-02T23:29:04Z | 2024-05-06T13:46:39Z | transformers | 119 | 0 | null | question-answering | {"parameters": {"F32": 66364418}, "total": 66364418} | [
".gitattributes",
"384-8bits.tflite",
"384-fp16.tflite",
"384.tflite",
"README.md",
"config.json",
"coreml_model.mlmodel",
"coreml_model_fp16.mlmodel",
"model.safetensors",
"pytorch_model.bin",
"saved_model.tar.gz",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | dfb8fa0e03905f0b6ea92133e56b6fef138015f2 | [
"transformers",
"pytorch",
"tf",
"tflite",
"coreml",
"safetensors",
"distilbert",
"question-answering",
"en",
"dataset:squad",
"arxiv:1910.01108",
"arxiv:1910.09700",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertForQuestionAnswering"], "model_type": "distilbert", "tokenizer_config": {}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad"], "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, "widget": [{"text": "Which name is also used to describe the Amazon rain... | # DistilBERT base uncased distilled SQuAD
## Table of Contents
- [Model Details](#model-details)
- [How To Get Started With the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environmenta... | null | [
"apache-2.0"
] | [
"squad"
] | [
"en"
] | 66,364,418 | null | null | [
"AutoModelForQuestionAnswering",
"distilbert",
"DistilBertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174349 | distilbert/distilroberta-base | distilbert | null | 1,285,080 | 127,128,874 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:09:58Z | transformers | 174 | 0 | null | fill-mask | {"parameters": {"F32": 82760793}, "total": 82760793} | [
".gitattributes",
"README.md",
"config.json",
"dict.txt",
"flax_model.msgpack",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"rust_model.ot",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | fb53ab8802853c8e4fbdbcd0529f21fc6f459b2b | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"roberta",
"fill-mask",
"exbert",
"en",
"dataset:openwebtext",
"arxiv:1910.01108",
"arxiv:1910.09700",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "model_type": "roberta", "tokenizer_config": {}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["openwebtext"], "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": ["exbert"]} | # Model Card for DistilRoBERTa base
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training Details](#training-details)
5. [Evaluation](#evaluation)
6. [Environmental Impact](#environmental-impact)
7. [Citation](#citation)
8. ... | null | [
"apache-2.0"
] | [
"openwebtext"
] | [
"en"
] | 82,760,793 | null | null | [
"roberta",
"AutoModelForMaskedLM",
"RobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17434a | openai-community/gpt2-large | openai-community | null | 3,114,433 | 51,120,858 | False | 2022-03-02T23:29:04Z | 2024-02-19T11:11:02Z | transformers | 348 | 0 | null | text-generation | {"parameters": {"F32": 811778816}, "total": 811778816} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"generation_config.json",
"generation_config_for_text_generation.json",
"merges.txt",
"model.safetensors",
"onnx/Constant_164_attr__value",
"onnx/Constant_174_attr__value",
"onnx/config.json",
"onnx/decoder_model.onnx",
"onn... | 32b71b12589c2f8d625668d2335a01cac3249519 | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"onnx",
"safetensors",
"gpt2",
"text-generation",
"en",
"arxiv:1910.09700",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {}} | {
"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": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # GPT-2 Large
## Table of Contents
- [Model Details](#model-details)
- [How To Get Started With the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environmental Impact](#environmental-imp... | null | [
"mit"
] | null | [
"en"
] | 811,778,816 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17434b | openai-community/gpt2-medium | openai-community | null | 684,262 | 26,579,081 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:39:04Z | transformers | 197 | 0 | null | text-generation | {"parameters": {"F32": 379988992}, "total": 379988992} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"generation_config.json",
"generation_config_for_text_generation.json",
"merges.txt",
"model.safetensors",
"onnx/config.json",
"onnx/decoder_model.onnx",
"onnx/decoder_model_merged.onnx",
"onnx/decoder_with_past_model.onnx",
... | 6dcaa7a952f72f9298047fd5137cd6e4f05f41da | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"onnx",
"safetensors",
"gpt2",
"text-generation",
"en",
"arxiv:1910.09700",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {}} | {
"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": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # GPT-2 Medium
## Model Details
**Model Description:** GPT-2 Medium is the **355M parameter** version of GPT-2, a transformer-based language model created and released by OpenAI. The model is a pretrained model on English language using a causal language modeling (CLM) objective.
- **Developed by:** OpenAI, see [as... | null | [
"mit"
] | null | [
"en"
] | 379,988,992 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17434c | openai-community/gpt2-xl | openai-community | null | 218,521 | 15,944,717 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:39:12Z | transformers | 376 | 0 | null | text-generation | {"parameters": {"F32": 1607942848}, "total": 1607942848} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"generation_config.json",
"generation_config_for_text_generation.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"rust_model.ot",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 15ea56dee5df4983c59b2538573817e1667135e2 | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"gpt2",
"text-generation",
"en",
"arxiv:1910.09700",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {}} | {
"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": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # GPT-2 XL
## Table of Contents
- [Model Details](#model-details)
- [How To Get Started With the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environmental Impact](#environmental-impact... | null | [
"mit"
] | null | [
"en"
] | 1,607,942,848 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17434e | openai-community/openai-gpt | openai-community | null | 254,933 | 6,475,203 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:39:20Z | transformers | 289 | 0 | null | text-generation | {"parameters": {"F32": 119680512}, "total": 119680512} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"generation_config_for_text_generation.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"rust_model.ot",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 1e0d4f3028acbffb47fe933cea64619c5ec1a002 | [
"transformers",
"pytorch",
"tf",
"rust",
"safetensors",
"openai-gpt",
"text-generation",
"en",
"arxiv:1705.11168",
"arxiv:1803.02324",
"arxiv:1910.09700",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["OpenAIGPTLMHeadModel"], "model_type": "openai-gpt", "tokenizer_config": {}} | {
"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": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # OpenAI GPT 1
## Table of Contents
- [Model Details](#model-details)
- [How To Get Started With the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environmental Impact](#environmental-im... | null | [
"mit"
] | null | [
"en"
] | 119,680,512 | null | null | [
"openai-gpt",
"OpenAIGPTLMHeadModel",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17434f | openai-community/roberta-base-openai-detector | openai-community | null | 867,428 | 7,037,343 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:46:55Z | transformers | 132 | 0 | null | text-classification | {"parameters": {"F32": 125237762}, "total": 125237762} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 6cba99c003b711c7fe94f8a3aa2be35a792cb6fa | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"roberta",
"text-classification",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1904.09751",
"arxiv:1910.09700",
"arxiv:1908.09203",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"deplo... | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "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": ["exbert"]} | # RoBERTa Base OpenAI Detector
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environmental Impact](#environmental-impact)
- [Technical Specifications](#technical-specificatio... | null | [
"mit"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 125,237,762 | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174351 | FacebookAI/roberta-large-mnli | FacebookAI | null | 326,638 | 23,521,392 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:47:11Z | transformers | 210 | 0 | null | text-classification | {"parameters": {"F32": 356412419}, "total": 356412419} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 2a8f12d27941090092df78e4ba6f0928eb5eac98 | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"roberta",
"text-classification",
"autogenerated-modelcard",
"en",
"dataset:multi_nli",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:1806.02847",
"arxiv:1804.07461",
"arxiv:1704.05426",
"arxiv:1508.05326"... | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["multi_nli", "wikipedia", "bookcorpus"], "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": ["autogenerated-modelcard"]} | # roberta-large-mnli
## Table of Contents
- [Model Details](#model-details)
- [How To Get Started With the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation-results)
- [Environmental Impact](#en... | null | [
"mit"
] | [
"multi_nli",
"wikipedia",
"bookcorpus"
] | [
"en"
] | 356,412,419 | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174352 | openai-community/roberta-large-openai-detector | openai-community | null | 7,822 | 2,754,235 | False | 2022-03-02T23:29:04Z | 2024-04-10T09:56:29Z | transformers | 29 | 0 | null | text-classification | {"parameters": {"F32": 356411394}, "total": 356411394} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 38f3e0ccf205e9c4e0b38ae9d75ec948141bf832 | [
"transformers",
"pytorch",
"jax",
"safetensors",
"roberta",
"text-classification",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1904.09751",
"arxiv:1910.09700",
"arxiv:1908.09203",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "tokenizer_config": {}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["bookcorpus", "wikipedia"], "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": ["exbert"]} | # RoBERTa Large OpenAI Detector
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environmental Impact](#environmental-impact)
- [Technical Specifications](#technical-specificati... | null | [
"mit"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | 356,411,394 | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174354 | google-t5/t5-11b | google-t5 | null | 21,353 | 8,401,584 | False | 2022-03-02T23:29:04Z | 2023-01-02T16:15:50Z | transformers | 69 | 0 | null | translation | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"spiece.model",
"tf_model.h5",
"tokenizer.json"
] | 90f37703b3334dfe9d2b009bfcbfbf1ac9d28ea3 | [
"transformers",
"pytorch",
"tf",
"t5",
"text-generation",
"summarization",
"translation",
"en",
"fr",
"ro",
"de",
"multilingual",
"dataset:c4",
"arxiv:1805.12471",
"arxiv:1708.00055",
"arxiv:1704.05426",
"arxiv:1606.05250",
"arxiv:1808.09121",
"arxiv:1810.12885",
"arxiv:1905.10... | null | {"architectures": ["T5WithLMHeadModel"], "model_type": "t5"} | {
"auto_model": "AutoModelWithLMHead",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["c4"], "eval_results": null, "language": ["en", "fr", "ro", "de", "multilingual"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["summarization", "translation"], "inference"... | # Model Card for T5 11B
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [B... | null | [
"apache-2.0"
] | [
"c4"
] | [
"en",
"fr",
"ro",
"de",
"multilingual"
] | null | null | null | [
"t5",
"T5WithLMHeadModel",
"AutoModelWithLMHead"
] | [
"translation",
"summarization",
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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