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classes | has_pre_tokenizer bool 2
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values | created_at timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-11-03 14:41:54 | last_modified timestamp[us, tz=UTC]date 2020-12-11 21:34:15 2026-03-29 10:14:05 ⌀ | library_name stringclasses 36
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
669207a83bd55e86d861533e | 39b1e434a495263c | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 349 | Magpie-Align/Llama-3-8B-Magpie-Align-SFT-v0.3 | Magpie-Align | {
"models": [
{
"_id": "661f97d48e7f3438386f755d",
"id": "meta-llama/Meta-Llama-3-8B"
}
],
"relation": "finetune"
} | 8,394 | 146,951 | False | 2024-07-13T04:50:48Z | 2024-07-19T20:33:26Z | transformers | 6 | 0 | [{"name": "Llama-3-8B-Magpie-Align-SFT-v0.3", "results": []}] | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
".gitattributes",
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"config.json",
"generation_config.json",
"model-00001-of-00004.safetensors",
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"pytorch_model-00001-of-00004.bin",
"pytorch_mod... | d2578eb754d1c20efe604749296580f680950917 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"axolotl",
"generated_from_trainer",
"conversational",
"en",
"zh",
"dataset:Magpie-Align/Magpie-Reasoning-150K",
"dataset:Magpie-Align/Magpie-Pro-MT-300K-v0.1",
"dataset:Magpie-Align/Magpie-Qwen2-Pro-200K-Chinese",
"arxi... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "meta-llama/Meta-Llama-3-8B", "datasets": ["Magpie-Align/Magpie-Reasoning-150K", "Magpie-Align/Magpie-Pro-MT-300K-v0.1", "Magpie-Align/Magpie-Qwen2-Pro-200K-Chinese"], "eval_results": [], "language": ["en", "zh"], "library_name": null, "license": "llama3", "license_name": null, "license_link": null, "met... | 
# 🐦 Llama-3-8B-Magpie-Align-SFT-v0.3
Project Web: [https://magpie-align.github.io/](https://magpie-align.github.io/)
Arxiv Technical Report: [https://arxiv.org/abs/2406.08464](https://arxiv.org/abs/24... | null | [
"llama3"
] | [
"Magpie-Align/Magpie-Reasoning-150K",
"Magpie-Align/Magpie-Pro-MT-300K-v0.1",
"Magpie-Align/Magpie-Qwen2-Pro-200K-Chinese"
] | [
"en",
"zh"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175efb | 4256c969642ce740 | 47b1b606cb314d14 | 30,000 | Unigram | null | true | true | true | true | 3 | Sequence | Metaspace | Metaspace | [
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 928 | IlyaGusev/rut5_base_sum_gazeta | IlyaGusev | null | 8,104 | 142,064 | False | 2022-03-02T23:29:04Z | 2022-07-13T15:36:04Z | transformers | 18 | 0 | null | summarization | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | f09a08cae5d74c70e55da1a6ebb49f88c26f433b | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"summarization",
"ru",
"dataset:IlyaGusev/gazeta",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["IlyaGusev/gazeta"], "eval_results": null, "language": ["ru"], "library_name": null, "license": ["apache-2.0"], "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["summarization", "t5"], "inference": {"parameters": {"no_repea... | # RuT5SumGazeta
## Model description
This is the model for abstractive summarization for Russian based on [rut5-base](https://huggingface.co/cointegrated/rut5-base).
## Intended uses & limitations
#### How to use
Colab: [link](https://colab.research.google.com/drive/1re5E26ZIDUpAx1gOCZkbF3hcwjozmgG0)
```python
f... | null | [
"apache-2.0"
] | [
"IlyaGusev/gazeta"
] | [
"ru"
] | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
648c0c0b270f79a8b452398f | 71140a663949f258 | 8a01c02d4d0a401c | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 9 | ylacombe/bark-small | ylacombe | null | 826 | 106,867 | False | 2023-06-16T07:15:23Z | 2023-07-18T08:11:24Z | transformers | 2 | 0 | null | text-to-speech | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model.bin",
"speaker_embeddings/announcer_coarse_prompt.npy",
"speaker_embeddings/announcer_fine_prompt.npy",
"speaker_embeddings/announcer_semantic_prompt.npy",
"speaker_embeddings/de_speaker_0_coarse_prompt.npy",
"s... | a5fe1d91a73caef7e0ac06a06a26baf7ba7fe8ad | [
"transformers",
"pytorch",
"bark",
"text-to-audio",
"audio",
"text-to-speech",
"en",
"de",
"es",
"fr",
"hi",
"it",
"ja",
"ko",
"pl",
"pt",
"ru",
"tr",
"zh",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BarkModel"], "model_type": "bark", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForTextToWaveform",
"custom_class": null,
"pipeline_tag": "text-to-audio",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "de", "es", "fr", "hi", "it", "ja", "ko", "pl", "pt", "ru", "tr", "zh"], "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["bark"... | # Bark
Bark is a transformer-based text-to-audio model created by [Suno](https://www.suno.ai).
Bark can generate highly realistic, multilingual speech as well as other audio - including music,
background noise and simple sound effects. The model can also produce nonverbal
communications like laughing, sighing and c... | null | [
"cc-by-nc-4.0"
] | null | [
"en",
"de",
"es",
"fr",
"hi",
"it",
"ja",
"ko",
"pl",
"pt",
"ru",
"tr",
"zh"
] | null | null | null | [
"AutoModelForTextToWaveform",
"BarkModel",
"bark"
] | [
"text-to-speech",
"text-to-audio"
] | [
"text",
"audio"
] | [
"text"
] | [
"audio"
] |
659319a97fe02354739a079b | 1c2b94bc65ea16ba | 7c4c85b636f4813b | 64,000 | BPE | 110,029 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 919 | jondurbin/bagel-dpo-34b-v0.2 | jondurbin | null | 8,611 | 147,510 | False | 2024-01-01T19:59:37Z | 2024-02-13T22:24:32Z | transformers | 97 | 0 | null | text-generation | {"parameters": {"BF16": 34388917248}, "total": 34388917248} | [
".gitattributes",
"README.md",
"bagel.png",
"config.json",
"model-00001-of-00015.safetensors",
"model-00002-of-00015.safetensors",
"model-00003-of-00015.safetensors",
"model-00004-of-00015.safetensors",
"model-00005-of-00015.safetensors",
"model-00006-of-00015.safetensors",
"model-00007-of-00015... | 79cd55df5caae7f61dfed74795cae16e66e6a345 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"dataset:ai2_arc",
"dataset:unalignment/spicy-3.1",
"dataset:codeparrot/apps",
"dataset:facebook/belebele",
"dataset:boolq",
"dataset:jondurbin/cinematika-v0.1",
"dataset:drop",
"dataset:lmsys/lmsys-chat-1m",
"dat... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<unk>", "unk_token": "<unk>", "use_default_system_prompt": false, "chat_template": "{%- for idx in range(0, messages|length) -%}\n{%- if messages[idx]['role'] == 'user' -%}\n{%- if ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["ai2_arc", "unalignment/spicy-3.1", "codeparrot/apps", "facebook/belebele", "boolq", "jondurbin/cinematika-v0.1", "drop", "lmsys/lmsys-chat-1m", "TIGER-Lab/MathInstruct", "cais/mmlu", "Muennighoff/natural-instructions", "openbookqa", "piqa", "Vezora/Tested-22k-Python-Alpaca", "cakiki/r... | # A bagel, with everything
## Overview
An experimental fine-tune of [yi-34b-200k](https://huggingface.co/01-ai/Yi-34B-200K) using [bagel](https://github.com/jondurbin/bagel)
This version also includes the toxic DPO dataset, and should have less censorship than it's counterparts. You may want to... | null | [
"other",
"yi-license",
"https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE"
] | [
"ai2_arc",
"unalignment/spicy-3.1",
"codeparrot/apps",
"facebook/belebele",
"boolq",
"jondurbin/cinematika-v0.1",
"drop",
"lmsys/lmsys-chat-1m",
"TIGER-Lab/MathInstruct",
"cais/mmlu",
"Muennighoff/natural-instructions",
"openbookqa",
"piqa",
"Vezora/Tested-22k-Python-Alpaca",
"cakiki/ros... | null | 34,388,917,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68e0addf59f86844ce4a461d | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | QuantTrio/Qwen3-VL-30B-A3B-Instruct-AWQ | QuantTrio | {
"models": [
{
"_id": "68dbb651542e04c5d9a90b86",
"id": "Qwen/Qwen3-VL-30B-A3B-Instruct"
}
],
"relation": "quantized"
} | 559,344 | 2,191,261 | False | 2025-10-04T05:17:19Z | 2025-10-08T14:25:49Z | transformers | 41 | 0 | null | text-generation | {"parameters": {"I32": 29896998912, "F16": 1173755120}, "total": 31070754032} | [
".gitattributes",
"README.md",
"chat_template.json",
"config.json",
"configuration.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00006.safetensors",
"model-00002-of-00006.safetensors",
"model-00003-of-00006.safetensors",
"model-00004-of-00006.safetensors",
"model-00005-of-0000... | a5ea10732e2c9330957864ece3ec66d806a4b00d | [
"transformers",
"safetensors",
"qwen3_vl_moe",
"image-text-to-text",
"AWQ",
"vLLM",
"text-generation",
"conversational",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen3-VL-30B-A3B-Instruct",
"base_model:quantized:Qwen/Qwen3-VL-30B-A3B-... | null | {"architectures": ["Qwen3VLMoeForConditionalGeneration"], "model_type": "qwen3_vl_moe", "quantization_config": {"quant_method": "awq", "bits": 4}, "processor_config": {"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {%- if messages[0].content is... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["Qwen/Qwen3-VL-30B-A3B-Instruct"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["AWQ", "vLLM"], "base_model_r... | null | null | [
"apache-2.0"
] | null | null | 31,070,754,032 | null | null | [
"AutoModelForImageTextToText",
"qwen3_vl_moe",
"Qwen3VLMoeForConditionalGeneration"
] | [
"image-text-to-text",
"text-generation"
] | [
"text",
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
677eb45408a874cc97cdd275 | 1774aa5af215e36a | 6b3612a55f8124d9 | 151,657 | BPE | 151,387 | true | true | true | true | 14 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 576 | llamaindex/vdr-2b-multi-v1 | llamaindex | {
"models": [
{
"_id": "66e14164d01557e65b7e0191",
"id": "MrLight/dse-qwen2-2b-mrl-v1"
}
],
"relation": "finetune"
} | 1,869 | 124,250 | False | 2025-01-08T17:22:28Z | 2025-05-21T15:32:02Z | sentence-transformers | 128 | 2 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.json",
"config.json",
"config_sentence_transformers.json",
"cover.png",
"custom_st.py",
"generation_config.json",
"merges.txt",
"model.safetensors",
"modules.json",
"ndcgtop.png",
"preprocessor_config.json",
"special_toke... | d6261a749ca2401ac4c88b72a818620cedc6d799 | [
"sentence-transformers",
"safetensors",
"qwen2_vl",
"image-text-to-text",
"transformers",
"Qwen2-VL",
"conversational",
"en",
"it",
"fr",
"de",
"es",
"dataset:llamaindex/vdr-multilingual-train",
"arxiv:2406.11251",
"base_model:MrLight/dse-qwen2-2b-mrl-v1",
"base_model:finetune:MrLight/... | null | {"architectures": ["Qwen2VLForConditionalGeneration"], "model_type": "qwen2_vl", "processor_config": {"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpfu... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["MrLight/dse-qwen2-2b-mrl-v1"], "datasets": ["llamaindex/vdr-multilingual-train"], "eval_results": null, "language": ["en", "it", "fr", "de", "es"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags... | # vdr-2b-multi-v1
vdr-2b-multi-v1 is a multilingual embedding model designed for visual document retrieval across multiple languages and domains. It encodes document page screenshots into dense single-vector representations, this will effectively allow to search and query visually rich multilingual doc... | null | [
"apache-2.0"
] | [
"llamaindex/vdr-multilingual-train"
] | [
"en",
"it",
"fr",
"de",
"es"
] | null | null | null | [
"AutoModelForImageTextToText",
"qwen2_vl",
"Qwen2VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
6540600750bdadb05b3b2dfe | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | NousResearch/Yarn-Mistral-7b-64k | NousResearch | null | 1,440 | 113,377 | False | 2023-10-31T02:01:43Z | 2023-11-02T19:00:04Z | transformers | 52 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_mistral.py",
"generation_config.json",
"modeling_mistral_yarn.py",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.jso... | 0273c624561fcecc8e8f4030492a9307aa60f945 | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"custom_code",
"en",
"dataset:emozilla/yarn-train-tokenized-16k-mistral",
"arxiv:2309.00071",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "auto_map": {"AutoConfig": "configuration_mistral.MistralConfig", "AutoModelForCausalLM": "modeling_mistral_yarn.MistralForCausalLM"}, "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_sy... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["emozilla/yarn-train-tokenized-16k-mistral"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["perplexity"], "model_name": null, "pipeline_tag": null, "tags": null} | # Model Card: Nous-Yarn-Mistral-7b-64k
[Preprint (arXiv)](https://arxiv.org/abs/2309.00071)
[GitHub](https://github.com/jquesnelle/yarn)
## Model Description
Nous-Yarn-Mistral-7b-64k is a state-of-the-art l... | null | [
"apache-2.0"
] | [
"emozilla/yarn-train-tokenized-16k-mistral"
] | [
"en"
] | null | null | [
"perplexity"
] | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | openbmb/UltraRM-13b | openbmb | null | 588 | 111,721 | False | 2023-09-22T09:34:58Z | 2023-10-14T09:49:47Z | transformers | 61 | 0 | null | null | null | [
".gitattributes",
"README.md",
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"modeling_llama_rm.py",
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"pytorch_model-00003-of-00003.bin",
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"tokenizer.mo... | a5b63d2f9531c25b65040981b4f2d8044e5fa378 | [
"transformers",
"pytorch",
"llama",
"dataset:openbmb/UltraFeedback",
"arxiv:2310.01377",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaRewardModel"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": false, "rstrip... | {
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} | {"base_model": null, "datasets": ["openbmb/UltraFeedback"], "eval_results": null, "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # News
- [2023/09/26]: UltraRM unleashes the power of [UltraLM-13B-v2.0](https://huggingface.co/openbmb/UltraLM-13b-v2.0) and [UltraLM-13B](https://huggingface.co/openbmb/UltraLM-13b)! A simple best-of-16 sampling achieves **92.30%** (UltraLM2, 🥇 in 13B results) and **91.54%** (UltraLM, 🥇 in LLaMA-1 results) win rat... | null | [
"mit"
] | [
"openbmb/UltraFeedback"
] | null | null | null | null | [
"llama",
"LlamaRewardModel",
"AutoModel"
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null
] | null | null | null |
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<picture>
<img src="https://raw.githubusercontent.com/01-ai/Yi/main/assets/img/Yi_logo_icon_light.svg" width="150px">
</picture>
</div>
<p align="center">
<a href="https://github.com/01-ai">🐙 GitHub</a> •
<a href="https://discord.gg/hYUwWddeAu">👾 Discord</a> •
<a href="https://twitter... | null | [
"apache-2.0"
] | null | null | 34,388,917,248 | null | null | [
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}
],
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} | 28,773 | 159,761 | False | 2025-02-14T14:25:04Z | 2025-08-27T12:35:05Z | transformers | 60 | 0 | null | automatic-speech-recognition | {"parameters": {"F16": 1609879040}, "total": 1609879040} | [
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} | {"base_model": "openai/whisper-large-v3", "datasets": ["KBLab/rixvox-v2"], "eval_results": null, "language": ["sv"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "automatic-speech-recognition", "tags": ["ctransl... | null | null | [
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641b598d5d3929663018cd92 | f56392a3c3b561ef | f26f356cd728caa8 | 49,408 | BPE | 48,894 | true | true | true | true | 2 | Sequence | Sequence | ByteLevel | [
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] | [
"Split",
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] | [
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] | 7 | Idan0405/ClipMD | Idan0405 | null | 10 | 105,111 | False | 2023-03-22T19:39:57Z | 2023-06-27T13:37:21Z | transformers | 8 | 0 | null | zero-shot-image-classification | null | [
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] | null | {"architectures": ["ClipMDModel"], "auto_map": {"AutoModel": "ClipMDModel.ClipMDModel"}, "model_type": "clip", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<|startoftext|>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "cont... | {
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "zero-shot-image-classification", "tags": ["medical"], "model_type": "clip", "inference": false} | # Model Card: ClipMD
## Model Details
ClipMD is a medical image-text matching model based on OpenAI's CLIP model with a sliding window text encoder.
### Model Description
The model uses a ViT-B/32 Transformer architecture as an image encoder and uses a masked sliding window elf-attention Transformer as a text encode... | null | null | null | [
"en"
] | null | null | null | [
"AutoModel",
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"embeddings"
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%... | null | [
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65d637611793b94e42bac5b1 | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
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] | 106 | unsloth/gemma-7b-it-bnb-4bit | unsloth | null | 711 | 111,094 | False | 2024-02-21T17:48:17Z | 2024-09-03T03:43:19Z | transformers | 15 | 0 | null | text-generation | {"parameters": {"F32": 526400, "BF16": 786607104, "U8": 7993362352}, "total": 8780495856} | [
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] | 954d1406115af7ef1d200569897447ea334d0000 | [
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"en",
"license:apache-2.0",
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"endpoints_compatible",
"4-bit",
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] | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not sup... | {
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We have a Google Colab Tesla T4 notebook for Gemma 7b here: https://colab.research.google.com/drive/10NbwlsRChbma1v55m8LAPYG15uQv6HLo?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.p... | null | [
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6594a8184a24a387789d3793 | 69d9860d38b5c798 | cf7a052aa6fec7ad | 30,000 | BPE | 15,977 | true | true | false | true | 229 | Sequence | Metaspace | Metaspace | [
"NFKC",
"BertNormalizer"
] | [
"Metaspace"
] | [
"Metaspace"
] | 282 | circulus/canvers-en2ko-v2 | circulus | null | 47 | 107,441 | False | 2024-01-03T00:19:36Z | 2024-01-03T00:25:39Z | transformers | 1 | 0 | null | null | {"parameters": {"F32": 123889968}, "total": 123889968} | [
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"gpl-3.0"
] | null | null | 123,889,968 | null | null | [
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62fec781578749fe22b2785b | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | KoboldAI/GPT-NeoX-20B-Skein | KoboldAI | null | 899 | 109,012 | False | 2022-08-18T23:13:05Z | 2022-09-26T19:19:21Z | transformers | 11 | 0 | null | text-generation | null | [
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"README.md",
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"pytorch_model-00001-of-00023.bin",
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"pytorch",
"gpt_neox",
"text-generation",
"en",
"arxiv:2204.06745",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # GPT-NeoX-20B-Skein
## Model description
Skein is a series of hybrid story generation models intended for use in both text adventure writing and normal novel-style writing. The models are known to possess a strong second person bias. For inquiries, please contact the KoboldAI community.
The name comes from the Integr... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
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"text"
] | [
"text"
] |
6610b53f50350afe76e2f902 | 0aea00f578e27edb | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 904 | Kquant03/CognitiveFusion2-4x7B-BF16 | Kquant03 | null | 8,492 | 146,072 | False | 2024-04-06T02:36:47Z | 2024-04-09T17:04:29Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"BF16": 24153690112}, "total": 24153690112} | [
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"en",
"arxiv:2101.03961",
"license:apache-2.0",
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] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<s>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["moe", "merge"], "thumbnail": "https://cdn-uploads.huggingface.co/production/upl... | # CognitiveFusion2-4x7B-BF16
# Back and better than ever.
[GGUF FILES](https://huggingface.co/Kquant03/CognitiveFusion2-4x7B-GGUF)
[Join our Discord!](https://discord.gg/uT4CzytfYW)
This is an ... | null | [
"apache-2.0"
] | null | [
"en"
] | 24,153,690,112 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
662b32a6c709a61df836819f | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | lightblue/suzume-llama-3-8B-multilingual-orpo-borda-top75 | lightblue | {
"models": [
{
"_id": "6627253888596f571aedfb4a",
"id": "lightblue/suzume-llama-3-8B-multilingual"
}
],
"relation": "finetune"
} | 7,845 | 142,560 | False | 2024-04-26T04:50:46Z | 2024-05-30T09:57:29Z | transformers | 4 | 0 | [{"name": "workspace/llm_training/axolotl/llama3-multilingual-orpo/output_mitsu_top75_borda", "results": []}] | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
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"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"... | 555f4a0092f239557e1aa34f9d489e8156b907bb | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"conversational",
"arxiv:2405.18952",
"base_model:lightblue/suzume-llama-3-8B-multilingual",
"base_model:finetune:lightblue/suzume-llama-3-8B-multilingual",
"license:cc-by-nc-4.0",
"text-generation-inference",
... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "lightblue/suzume-llama-3-8B-multilingual", "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "workspace/llm_training/axolotl/llama3-multilingual-orpo/output_mitsu_top75_borda... | # Suzume ORPO
<p align="center">
<img width=500 src="https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/kWQSu02YfgYdUQqv4s5lq.png" alt="Suzume with Mitsu - a Japanese tree sparrow with honey on it"/>
</p>
[[Paper]](https://arxiv.org/abs/2405.18952) [[Dataset]](https://huggingface.co/data... | null | [
"cc-by-nc-4.0"
] | null | null | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63e4a0d5477016c4b819459e | 30094a1eabdbef67 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 4 | FredZhang7/anime-anything-promptgen-v2 | FredZhang7 | null | 974 | 107,545 | False | 2023-02-09T07:29:25Z | 2023-03-16T19:33:55Z | transformers | 62 | 0 | null | text-generation | {"parameters": {"F32": 81912576, "U8": 6291456}, "total": 88204032} | [
".gitattributes",
"README.md",
"anime_boy_settings.txt",
"anime_boys.png",
"anime_girl_settings.txt",
"anime_girls.png",
"blacklist.txt",
"config.json",
"contrastive_search.png",
"model.safetensors",
"preprocess.py",
"pytorch_model.bin",
"tokenizer.json"
] | 0b3297c092ac2ecc9f1a336b8762642af540a7c4 | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"stable-diffusion",
"anime",
"anything-v4",
"art",
"arxiv:2210.14140",
"en",
"dataset:FredZhang7/anime-prompts-180K",
"license:creativeml-openrail-m",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure... | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2"} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["FredZhang7/anime-prompts-180K"], "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": ["stable-diffusion", "anime", "anything-v... | ## Fast Anime PromptGen
This model was trained on a dataset of **80,000** safe anime prompts for 3 epochs. I fetched the prompts from the [Safebooru API endpoint](https://safebooru.donmai.us/posts/random.json), but only accepted unique prompts with **up_score ≥ 8** and without any [blacklisted tags](./blacklist.txt). ... | null | [
"creativeml-openrail-m"
] | [
"FredZhang7/anime-prompts-180K"
] | [
"en"
] | 88,204,032 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
667a6b19822fddf992bf20c9 | 3f287b04362fff24 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 158 | UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter2 | UCLA-AGI | null | 8,398 | 145,720 | False | 2024-06-25T07:00:41Z | 2024-06-25T07:57:15Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00004.bin",
"pytorch_model-00002-of-00004.bin",
"pytorch_model-00003-of-00004.bin",
"pytorch_model-00004-of-00004.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"... | 730c7207d4b538feeb3c2e6d6f6a6ba8615a9be3 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"conversational",
"en",
"dataset:openbmb/UltraFeedback",
"arxiv:2405.00675",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["openbmb/UltraFeedback"], "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} | Self-Play Preference Optimization for Language Model Alignment (https://arxiv.org/abs/2405.00675)
# Llama-3-Instruct-8B-SPPO-Iter2
This model was developed using [Self-Play Preference Optimization](https://arxiv.org/abs/2405.00675) at iteration 2, based on the [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface... | null | [
"apache-2.0"
] | [
"openbmb/UltraFeedback"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1802cb | 35f8a93a304f6b78 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 6 | sentence-transformers/msmarco-distilroberta-base-v2 | sentence-transformers | null | 678 | 109,323 | False | 2022-03-02T23:29:05Z | 2025-03-06T13:30:25Z | sentence-transformers | 3 | 0 | null | sentence-similarity | {"parameters": {"I64": 514, "F32": 82118400}, "total": 82118914} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"flax_model.msgpack",
"merges.txt",
"model.safetensors",
"modules.json",
"onnx/model.onnx",
"onnx/model_O1.onnx",
"onnx/model_O2.onnx",
"onnx/model_O3.onnx",
"onnx/model_O4.onnx",
... | d52faad9cd25c72533ec2df15bea947d2ba9bfbe | [
"sentence-transformers",
"pytorch",
"tf",
"jax",
"onnx",
"safetensors",
"openvino",
"roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaModel"], "model_type": "roberta", "tokenizer_config": {"unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": t... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "sentence-transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction",... | # sentence-transformers/msmarco-distilroberta-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy w... | null | [
"apache-2.0"
] | null | null | 82,118,914 | null | null | [
"roberta",
"AutoModel",
"RobertaModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
63571018d5389a0786fec264 | e44bb73a296dea43 | 2645a2484042bec8 | 50,297 | BPE | 50,000 | false | true | true | true | 41 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 930 | LegionIntel/yurts-python-code-gen-30-sparse | LegionIntel | null | 331 | 105,739 | False | 2022-10-24T22:22:16Z | 2022-10-27T20:39:18Z | transformers | 20 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | c79e4307e4a167ece0e914fd0325f1ca7e6ddc2c | [
"transformers",
"pytorch",
"codegen",
"text-generation",
"license:bsd-3-clause",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["CodeGenForCausalLM"], "model_type": "codegen", "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|pad|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "bsd-3-clause", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | null | [
"bsd-3-clause"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"codegen",
"CodeGenForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
665dc74c5baf7febc7b1975a | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/Qwen2-72B-Instruct-GPTQ-Int8 | Qwen | {
"models": [
{
"_id": "66555421d17e141dcb225f7f",
"id": "Qwen/Qwen2-72B-Instruct"
}
],
"relation": "quantized"
} | 63 | 104,598 | False | 2024-06-03T13:38:20Z | 2024-08-21T10:26:12Z | transformers | 15 | 0 | null | text-generation | {"parameters": {"I32": 70464307200, "F16": 2499616768}, "total": 72963923968} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00020.safetensors",
"model-00002-of-00020.safetensors",
"model-00003-of-00020.safetensors",
"model-00004-of-00020.safetensors",
"model-00005-of-00020.safetensors",
"model-00006-of-0... | f520efa3f3151d857441677d544da7bb960ca7d4 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2309.00071",
"base_model:Qwen/Qwen2-72B-Instruct",
"base_model:quantized:Qwen/Qwen2-72B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"8-bit",
"gptq",
"r... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 8, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|i... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2-72B-Instruct", "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "other", "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen2-72B-Instruct-GPTQ-Int8/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_t... | # Qwen2-72B-Instruct-GPTQ-Int8
## Introduction
Qwen2 is the new series of Qwen large language models. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the instruction-tuned 7... | null | [
"other",
"tongyi-qianwen",
"https://huggingface.co/Qwen/Qwen2-72B-Instruct-GPTQ-Int8/blob/main/LICENSE"
] | null | [
"en"
] | 72,963,923,968 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63d10bbd119416cdbe0d7afe | de0f98cd504e94de | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 317 | kabita-choudhary/finetuned-bart-for-conversation-summary | kabita-choudhary | null | 24 | 105,224 | False | 2023-01-25T11:00:13Z | 2023-01-26T12:09:46Z | transformers | 53 | 0 | [{"name": "bart-large-cnn-samsum", "results": [{"task": {"type": "summarization", "name": "Conversation Summarization"}, "dataset": {"name": "SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization", "type": "samsum"}, "metrics": [{"type": "rogue-1", "value": 54.8764, "name": "Validation ROGUE-1... | summarization | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 702abeb4d99b5255c099344410cc729892433490 | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"summarization",
"dataset:samsum",
"model-index",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BartForConditionalGeneration"], "model_type": "bart", "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": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["samsum"], "pipeline_tag": "summarization", "widget": [{"text": "Laurie: So, what are your plans for this weekend?\nChristie: I don\u2019t know. Do you want to get together or something?\nSarah: How about going to see a movie? Cinemax 26 on Carson Boulevard is showing Enchanted. Laurie: That sounds like a... | null | null | [
"samsum"
] | null | null | null | null | [
"bart",
"BartForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] | |
64c0d79ea20269b8bd897534 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | TheBloke/Llama-2-7B-Chat-fp16 | TheBloke | null | 459 | 110,713 | False | 2023-07-26T08:21:50Z | 2023-07-26T08:27:22Z | transformers | 32 | 0 | null | text-generation | {"parameters": {"F16": 6738417664}, "total": 6738417664} | [
".gitattributes",
"LICENSE.txt",
"README.md",
"USE_POLICY.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model... | 4594bf11fd5c66a9021d20f5ae5f3a246ce388a1 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"llama-2",
"en",
"arxiv:2307.09288",
"text-generation-inference",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": false, "rstrip... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["facebook", "meta", "pytorch", "llama", "llama-2"], "extra_gated_heading": ... | # **Llama 2**
Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 7B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be fo... | null | null | null | [
"en"
] | 6,738,417,664 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68c0b5d60858d7276b6312a9 | 5499fef3506cd876 | cf1efbe71ef28fc9 | 50,368 | BPE | 50,009 | true | true | true | true | 116 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 48 | thebajajra/RexBERT-micro | thebajajra | null | 244 | 105,166 | False | 2025-09-09T23:18:46Z | 2026-02-05T02:31:46Z | transformers | 4 | 0 | null | fill-mask | {"parameters": {"F32": 16913600}, "total": 16913600} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 25587117376236b769710249fdcb66d6041edcee | [
"transformers",
"pytorch",
"safetensors",
"modernbert",
"fill-mask",
"ecommerce",
"e-commerce",
"retail",
"marketplace",
"shopping",
"amazon",
"ebay",
"alibaba",
"google",
"rakuten",
"bestbuy",
"walmart",
"flipkart",
"wayfair",
"shein",
"target",
"etsy",
"shopify",
"tao... | null | {"architectures": ["ModernBertForMaskedLM"], "model_type": "modernbert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["thebajajra/Ecom-niverse"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "fill-mask", "tags": ["ecommerce", "e-commerce", "retail", "ma... | # RexBERT-micro
[](https://www.apache.org/licenses/LICENSE-2.0)
[](https://huggingface.co/collections/thebajajra/rexbert-68cc4b1b8a272f6beae5ebb8)
[![Data](https://img.sh... | null | [
"apache-2.0"
] | [
"thebajajra/Ecom-niverse"
] | [
"en"
] | 16,913,600 | null | null | [
"ModernBertForMaskedLM",
"modernbert",
"AutoModelForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f17979b | 44a4e69fe0b67f22 | 5f9f736c7dc6fbfa | 28,996 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 931 | batterydata/batterybert-cased-squad-v1 | batterydata | null | 79 | 1,181,247 | False | 2022-03-02T23:29:05Z | 2022-03-05T13:50:54Z | transformers | 0 | 0 | null | question-answering | null | [
".gitattributes",
"README.md",
"config.json",
"optimizer.pt",
"pytorch_model.bin",
"rng_state_0.pth",
"rng_state_1.pth",
"rng_state_2.pth",
"rng_state_3.pth",
"rng_state_4.pth",
"rng_state_5.pth",
"rng_state_6.pth",
"rng_state_7.pth",
"scheduler.pt",
"special_tokens_map.json",
"tokeniz... | f420944bc55b1d1d81112df9ca8609c33578693a | [
"transformers",
"pytorch",
"bert",
"question-answering",
"en",
"dataset:squad",
"dataset:batterydata/battery-device-data-qa",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForQuestionAnswering"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad", "batterydata/battery-device-data-qa"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": "squad", "model_name": null, "pipeline_tag": null, "tags": null} | # BatteryBERT-cased for QA
**Language model:** batterybert-cased
**Language:** English
**Downstream-task:** Extractive QA
**Training data:** SQuAD v1
**Eval data:** SQuAD v1
**Code:** See [example](https://github.com/ShuHuang/batterybert)
**Infrastructure**: 8x DGX A100
## Hyperparameters
```
batch_siz... | null | [
"apache-2.0"
] | [
"squad",
"batterydata/battery-device-data-qa"
] | [
"en"
] | null | null | [
"squad"
] | [
"AutoModelForQuestionAnswering",
"bert",
"BertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
630f047ca119d49bc1dda73b | 33abd493070ef5bc | 36f3edd369286eb9 | 46,145 | BPE | 45,899 | false | true | true | true | 4 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 932 | Langboat/bloom-1b4-zh | Langboat | null | 4,605 | 125,300 | False | 2022-08-31T06:49:32Z | 2023-05-08T03:39:33Z | transformers | 19 | 0 | null | text-generation | {"parameters": {"F32": 1397616640}, "total": 1397616640} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | cd76063fd0cde2b9bcc02901fcabd35ba71eff39 | [
"transformers",
"pytorch",
"safetensors",
"bloom",
"text-generation",
"zh",
"license:bigscience-bloom-rail-1.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BloomForCausalLM"], "model_type": "bloom", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": "bigscience-bloom-rail-1.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "widget": [{"text": "\u4e2d\u56fd\u7684\u9996\u... | This model is based on [bigscience/bloom-1b7](https://huggingface.co/bigscience/bloom-1b7).
We pruned its vocabulary from 250880 to 46145 with Chinese corpus to reduce GPU memory usage. So the total parameter is 1.4b now.
# How to use
```python
from transformers import BloomTokenizerFast, BloomForCausalLM
tokenizer... | null | [
"bigscience-bloom-rail-1.0"
] | null | [
"zh"
] | 1,397,616,640 | null | null | [
"AutoModelForCausalLM",
"BloomForCausalLM",
"bloom"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
661ef10af5182fafaf6588f6 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | GritLM/GritLM-7B-KTO | GritLM | null | 8,364 | 144,709 | False | 2024-04-16T21:43:38Z | 2024-06-14T13:44:17Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"global_step3500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt",
"global_step3500/bf16_zero_pp_rank_1_mp_rank_00_optim_states.pt",
"global_step3500/bf16_zero_pp_rank_2_mp_rank_00_optim_states.pt",
"global_step3500/bf16_zero_pp_ra... | b5c48669508c1de18c698460c187f64e90e7df44 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"custom_code",
"dataset:GritLM/tulu2",
"arxiv:2402.01306",
"arxiv:2402.09906",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "auto_map": {"AutoModel": "GritLM/GritLM-7B--modeling_gritlm7b.MistralModel", "AutoModelForCausalLM": "GritLM/GritLM-7B--modeling_gritlm7b.MistralForCausalLM", "AutoModelForSequenceClassification": "GritLM/GritLM-7B--modeling_gritlm7b.MistralForSequenceClassification"}, "model_... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["GritLM/tulu2"], "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, "inference": true} | # Model Summary
A [**KTO**](https://arxiv.org/abs/2402.01306) version of https://huggingface.co/GritLM/GritLM-7B
> GritLM is a generative representational instruction tuned language model. It unifies text representation (embedding) and text generation into a single model achieving state-of-the-art performance on both... | null | [
"apache-2.0"
] | [
"GritLM/tulu2"
] | null | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
645eb404340d0b66d1446543 | 30094a1eabdbef67 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 4 | roneneldan/TinyStories-8M | roneneldan | null | 9,278 | 131,172 | False | 2023-05-12T21:47:48Z | 2023-05-17T22:12:27Z | transformers | 5 | 0 | null | text-generation | null | [
".gitattributes",
"config.json",
"merges.txt",
"pytorch_model.bin",
"readme.md",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 8612e3b15c66ffa94eaa6ee0de5c96edd2d630af | [
"transformers",
"pytorch",
"gpt_neo",
"text-generation",
"endpoints_compatible",
"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": "<|endoftext|>", "lstrip": false, "normal... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"gpt_neo",
"AutoModelForCausalLM",
"GPTNeoForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65e8c443f433542879333a2b | a7b0a99838360123 | cad4902422b140fb | 64,000 | BPE | 110,029 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 933 | abacusai/bigyi-15b | abacusai | {
"models": [
{
"_id": "65e16e58d997c34a9ec70449",
"id": "01-ai/Yi-9B"
}
],
"relation": "finetune"
} | 7,988 | 142,054 | False | 2024-03-06T19:30:11Z | 2024-03-07T05:25:29Z | transformers | 11 | 0 | null | text-generation | {"parameters": {"F16": 15058243584}, "total": 15058243584} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"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.json",
"tokenizer.... | 5ec2656b39515e3a903adfb05e5022b0f4eb5e2a | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"base_model:01-ai/Yi-9B",
"base_model:finetune:01-ai/Yi-9B",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<unk>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["01-ai/Yi-9B"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "other", "license_name": "yi-license", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["mergekit", "merge"]} | # bigyi-15b
I recently made [bigstral-12b](https://huggingface.co/abacusai/bigstral-12b-32k) and then I saw this new awesome model [yi-9b](https://huggingface.co/01-ai/Yi-9B) and decided to make an embiggened version.
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mer... | null | [
"other",
"yi-license",
"LICENSE"
] | null | null | 15,058,243,584 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
643dc4dc8f6f0a641357175b | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | stabilityai/stablelm-base-alpha-3b | stabilityai | null | 5,017 | 116,449 | False | 2023-04-17T22:14:52Z | 2023-10-19T04:58:32Z | transformers | 82 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 819657db42861818efac86e8ca60f673fa912ef8 | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"causal-lm",
"en",
"license:cc-by-sa-4.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": ["cc-by-sa-4.0"], "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["causal-lm"]} | # StableLM-Base-Alpha
📢 **DISCLAIMER**: The StableLM-Base-Alpha models have been superseded. Find the latest versions in the Stable LM Collection [here](https://huggingface.co/collections/stabilityai/stable-lm-650852cfd55dd4e15cdcb30a).
## Model Description
`StableLM-Base-Alpha` is a suite of 3B and 7B parameter de... | null | [
"cc-by-sa-4.0"
] | null | [
"en"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67ff9385c795b579b14acf5b | b647996d6543f730 | 7ab62ce4e32550df | 151,674 | BPE | 151,387 | true | true | true | true | 31 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 172 | OpenGVLab/InternVL3-8B-Instruct | OpenGVLab | {
"models": [
{
"_id": "6800b1b051f13ac38199f916",
"id": "OpenGVLab/InternVL3-8B-Pretrained"
}
],
"relation": "finetune"
} | 71,235 | 258,957 | False | 2025-04-16T11:24:53Z | 2025-09-11T12:50:16Z | transformers | 13 | 0 | null | image-text-to-text | {"parameters": {"BF16": 7944373760}, "total": 7944373760} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_intern_vit.py",
"configuration_internvl_chat.py",
"conversation.py",
"examples/image1.jpg",
"examples/image2.jpg",
"examples/red-panda.mp4",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safeten... | ddb3a169d5582e5c76e0809a128e55ab63686ada | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"internvl",
"custom_code",
"image-text-to-text",
"conversational",
"multilingual",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.10442",
"arxiv:2504.10479",
"arxiv:2412.09616",
"base_model:O... | null | {"architectures": ["InternVLChatModel"], "auto_map": {"AutoConfig": "configuration_internvl_chat.InternVLChatConfig", "AutoModel": "modeling_internvl_chat.InternVLChatModel", "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel"}, "model_type": "internvl_chat", "tokenizer_config": {"bos_token": null, "chat... | {
"auto_model": "AutoModel",
"custom_class": "modeling_internvl_chat.InternVLChatModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["OpenGVLab/InternVL3-8B-Pretrained"], "datasets": null, "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "apache-2.0", "license_name": "qwen", "license_link": "https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE", "metrics": null, "model_name"... | # InternVL3-8B-Instruct
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggingface... | null | [
"apache-2.0",
"qwen",
"https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE"
] | null | [
"multilingual"
] | 7,944,373,760 | null | null | [
"AutoModel",
"internvl_chat",
"InternVLChatModel",
"modeling_internvl_chat.InternVLChatModel"
] | [
"image-text-to-text",
"feature-extraction"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text",
"embeddings"
] |
662e84fb04f9341b56dc3fca | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | MohamedRashad/Arabic-Orpo-Llama-3-8B-Instruct | MohamedRashad | null | 3,866 | 326,660 | False | 2024-04-28T17:18:51Z | 2024-05-03T12:57:47Z | transformers | 17 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"... | 36259c5e4cda0236b94dfef2b503f0b7635a3082 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"ar",
"dataset:2A2I/argilla-dpo-mix-7k-arabic",
"license:llama3",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["2A2I/argilla-dpo-mix-7k-arabic"], "eval_results": null, "language": ["ar"], "library_name": "transformers", "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | # 👳 Arabic ORPO LLAMA 3
<center>
<img src="https://cdn-uploads.huggingface.co/production/uploads/6116d0584ef9fdfbf45dc4d9/3ns3O_bWYxKEXmozA073h.png">
</center>
## 👓 Story first
This model is the a finetuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruc... | null | [
"llama3"
] | [
"2A2I/argilla-dpo-mix-7k-arabic"
] | [
"ar"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65a328bec0e637bd9c038909 | 0aea00f578e27edb | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 904 | rombodawg/Everyone-Coder-4x7b-Base | rombodawg | null | 8,478 | 144,974 | False | 2024-01-14T00:20:14Z | 2024-01-23T18:19:14Z | transformers | 42 | 0 | null | text-generation | {"parameters": {"F16": 24153690112}, "total": 24153690112} | [
".gitattributes",
"README.md",
"config.json",
"mergekit_moe_config.yml",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
"model.safetensors.index.json",
"special_to... | 5e4757ee9875ee65df9216dcc61208bd504d4632 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"merge",
"moe",
"license:cc-by-4.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<s>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["merge", "moe"]} | Everyone-Coder-4x7b-Base
EveryoneLLM series of models are a new Mixtral type model created using experts that were finetuned by the community, for the community. This is the first model to release... | null | [
"cc-by-4.0"
] | null | null | 24,153,690,112 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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# MaziyarPanahi/Calme-4x7B-MoE-v0.1
## Model Description
Calme-4x7B is a Mixture of Experts (MoE) model, integrating four state-of-the-art Calme-7B models. Essentially, Calme-4x7B is co... | null | [
"apache-2.0"
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64f87789e7584abc625712dc | 71140a663949f258 | 8a01c02d4d0a401c | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
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] | 9 | numind/NuNER-multilingual-v0.1 | numind | null | 6,181 | 133,451 | False | 2023-09-06T12:58:49Z | 2024-03-15T13:03:34Z | transformers | 70 | 0 | null | token-classification | null | [
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"Multilingual Bert",
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"de",
"it",
"es",
"pt",
"pl",
"nl",
"ru",
"arxiv:2402.15343",
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"deploy:azu... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "fr", "de", "it", "es", "pt", "pl", "nl", "ru"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "token-classification", "tags": ["token-classification... | # SOTA Entity Recognition Multilingual Foundation Model by NuMind 🔥
This model provides the best embedding for the Entity Recognition task and supports 9+ languages.
**Checkout other models by NuMind:**
* SOTA Entity Recognition Foundation Model in English: [link](https://huggingface.co/numind/entity-recognition-ge... | null | [
"mit"
] | null | [
"en",
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"es",
"pt",
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GGUF Format is ready at [cloudyu/Yi-34Bx2-MoE-60B-GGUF](https://huggingface.co/cloudyu/Yi-34Bx2-MoE-60B-GGUF)
# Yi based MOE 2x34B with mixtral architecture
Highest score Model ranked by Open LLM Leaderboard (2024-01-11)
* [Average Score 76.72](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboa... | null | [
"apache-2.0"
] | null | null | 60,813,892,608 | null | null | [
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6253dd2927a8414d3bbee8dc | ee381dce9a5e5009 | 4e4b4d176d158b96 | 25,004 | Unigram | null | true | true | true | true | 8 | Sequence | Metaspace | Metaspace | [
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] | 935 | peerapongch/baikal-sentiment-ball | peerapongch | null | 10 | 103,465 | False | 2022-04-11T07:47:53Z | 2022-04-11T07:57:59Z | transformers | 0 | 0 | null | text-classification | null | [
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] | c72e97733c3f42780150b112f3364328aa11a2f9 | [
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] | null | {"architectures": ["CamembertForSequenceClassification"], "model_type": "camembert", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": fals... | {
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] | null | 613 | dicta-il/dictabert-morph | dicta-il | null | 3,749 | 110,529 | False | 2023-08-29T17:24:14Z | 2025-01-19T20:59:09Z | transformers | 0 | 0 | null | feature-extraction | {"parameters": {"F32": 184395329}, "total": 184395329} | [
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] | 292587e0fd1d172fa0f487bae5b8befeab8bf568 | [
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"custom_code",
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] | null | {"architectures": ["BertForMorphTagging"], "auto_map": {"AutoModel": "BertForMorphTagging.BertForMorphTagging"}, "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["he"], "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "inference": false} | # DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew
State-of-the-art language model for Hebrew, released [here](https://arxiv.org/abs/2308.16687).
This is the fine-tuned model for the morphological tagging task.
For the bert-base models for other tasks, see [here](https://huggingface.co/collections/dicta-... | null | [
"cc-by-4.0"
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"he"
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] | [
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"Prepend",
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] | null | [
"Replace",
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] | 46 | pankajmathur/orca_mini_v3_70b | pankajmathur | null | 1,661 | 112,324 | False | 2023-08-10T02:28:29Z | 2025-03-17T15:16:14Z | transformers | 22 | 0 | [{"name": "orca_mini_v3_70b", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 71.25, "name": "norm... | text-generation | {"parameters": {"F16": 68976648192}, "total": 68976648192} | [
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} | {"datasets": ["psmathur/orca_mini_v1_dataset", "ehartford/dolphin"], "language": ["en"], "library_name": "transformers", "license": "other", "pipeline_tag": "text-generation", "model-index": [{"name": "orca_mini_v3_70b", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "A... | # orca_mini_v3_70b
**A Llama2-70b model trained on Orca Style datasets.**
<img src="https://huggingface.co/pankajmathur/orca_mini_v5_8b/resolve/main/orca_minis_small.jpeg" width="auto" />
<strong>
"Obsessed with GenAI's potential? So am I ! Let's create together 🚀 <a href="https://www.linkedin.com/in/pankajam" tar... | null | [
"other"
] | [
"psmathur/orca_mini_v1_dataset",
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"en"
] | 68,976,648,192 | null | null | [
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... | null | {"architectures": ["DebertaV2ForSequenceClassification"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
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} | {"base_model": null, "datasets": ["glue", "super_glue", "anli", "metaeval/babi_nli", "sick", "snli", "scitail", "hans", "alisawuffles/WANLI", "metaeval/recast", "sileod/probability_words_nli", "joey234/nan-nli", "pietrolesci/nli_fever", "pietrolesci/breaking_nli", "pietrolesci/conj_nli", "pietrolesci/fracas", "pietrole... | # Model Card for DeBERTa-v3-large-tasksource-nli
DeBERTa-v3-large fine-tuned with multi-task learning on 600 tasks of the [tasksource collection](https://github.com/sileod/tasksource/)
You can further fine-tune this model to use it for any classification or multiple-choice task.
This checkpoint has strong zero-shot va... | null | [
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<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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"ko",... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
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# Model Card for EuroLLM-1.7B
This is the model card for the first pre-trained model of the EuroLLM series: EuroLLM-1.7B. You can also check the instruction tuned version: [EuroLLM-1.7B-Instruct](https://huggingface.co/utter-project/EuroLLM-1.7B-Instruct).
- **Developed by:** Unb... | null | [
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "other", "license_name": "nvidia-open-model-license", "license_link": "https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf", "metrics": null, "model_na... | # Model Overview
Minitron-8B-Base is a large language model (LLM) obtained by pruning Nemotron-4 15B; specifically, we prune model embedding size, number of attention heads, and MLP intermediate dimension. Following pruning, we perform continued training with distillation using 94 billion tokens to arrive at the final... | null | [
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should probably proofread and complete it, then remove this comment. -->
# finetuning-financial-news-sentiment
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distil... | null | [
"apache-2.0"
] | null | null | null | null | [
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- **Model Architecture:** ApertusForCausalLM
- **Input:** Text
- **Output:** Text
- **Model Optimizations:**
- **Weight quantization:** FP8
- **Activation quantization:** FP8
- **Release Date:** 9/18/2025
- **Version:** 1.0
- **Model Developers:** Red Hat
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describe about pros and cons of docker system.
```
Answer:
Docker, a containerization platform, offers numerous advantages and potential drawbacks. Here's an overview of both aspects:
Pros (Advantages):
1. Isolation: Docker containers isolate applications from each other and their host systems, ensuring ... | null | [
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6567fb8105fb89fb7e307a90 | 82d0a1eeb1da9e53 | 50d2c83c17953b0f | 78,464 | BPE | 126,515 | true | false | true | true | 54 | Sequence | null | Sequence | [
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] | 938 | beomi/Yi-Ko-6B | beomi | null | 944 | 109,137 | False | 2023-11-30T03:03:29Z | 2024-07-08T01:17:27Z | transformers | 38 | 0 | [{"name": "Yi-Ko-6B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 48.89, "name": "normalized a... | text-generation | {"parameters": {"BF16": 6179524608}, "total": 6179524608} | [
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} | {"language": ["en", "ko"], "library_name": "transformers", "license": "apache-2.0", "pipeline_tag": "text-generation", "tags": ["pytorch", "Yi-Ko", "01-ai", "Yi"], "extra_gated_heading": "Access beomi/Yi-Ko-6B on Hugging Face", "extra_gated_button_content": "Submit", "extra_gated_fields": {"I agree to share my name, em... | > Update @ 2024.01.29 New Model [beomi/Yi-Ko-DUS-9B](https://huggingface.co/beomi/Yi-Ko-DUS-9B) Released! 🎉
> Update @ 2023.12.03 Yi-Ko(KoEN)-6B Achieved #1🥇 Pretrained Models at [Open Korean LLM Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)! 🎉
> Update @ 2023.12.01 Alpha Release of Y... | null | [
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] | 113 | rbhushan/distilgpt2-finetuned-wikitext2 | rbhushan | null | 18 | 102,970 | False | 2022-03-02T23:29:05Z | 2022-01-11T16:55:00Z | transformers | 0 | 0 | [{"name": "distilgpt2-finetuned-wikitext2", "results": []}] | text-generation | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilgpt2-finetuned-wikitext2
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the None ... | null | [
"apache-2.0"
] | null | null | null | null | null | [
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65ad257248c718a574d96484 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
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} | 7,910 | 141,098 | False | 2024-01-21T14:08:50Z | 2024-03-14T13:04:28Z | transformers | 10 | 0 | [{"name": "LogoS-7Bx2-MoE-13B-v0.1", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 74.49, "name"... | text-generation | {"parameters": {"BF16": 12879138816}, "total": 12879138816} | [
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} | {"base_model": ["yunconglong/Truthful_DPO_TomGrc_FusionNet_7Bx2_MoE_13B", "TomGrc/FusionNet_7Bx2_MoE_14B"], "language": ["en", "es"], "license": "apache-2.0", "tags": ["moe", "merge"], "model-index": [{"name": "LogoS-7Bx2-MoE-13B-v0.1", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "datas... | # LogoS-7Bx2-MoE-13B-v0.1
Model built by @RubielLabarta using SLERP merge method. The model is release for research purposes only, commercial use is not allowed.
The LogoS is a model to experiment with the MoE method, which could significantly increase the performance of the original model. The model has 12.9B parame... | null | [
"apache-2.0"
] | null | [
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"deploy:azure",
"region:us"
] | null | {"architectures": ["OPTForCausalLM"], "model_type": "opt", "tokenizer_config": {}} | {
"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": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["galactica"], "widget": [{"text": "The Transformer architecture [START_REF]"}, {... | 
# GALACTICA 6.7B (standard)
Model card from the original [repo](https://github.com/paperswithcode/galai/blob/main/docs/model_card.md)
Following [Mitchell et al. (2018)](https://arxiv.org/abs/1810.03993), this mod... | null | [
"cc-by-nc-4.0"
] | null | null | null | null | null | [
"OPTForCausalLM",
"AutoModelForCausalLM",
"opt"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17add4 | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | facebook/data2vec-text-base | facebook | null | 1,424 | 107,632 | False | 2022-03-02T23:29:05Z | 2022-04-18T16:03:20Z | transformers | 12 | 0 | null | feature-extraction | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | bd0db19c3500ee7a0b626791db67fa6e9fda9a0b | [
"transformers",
"pytorch",
"data2vec-text",
"feature-extraction",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:2202.03555",
"arxiv:1806.02847",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Data2VecTextModel"], "model_type": "data2vec-text", "tokenizer_config": {"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "norm... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"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"]} | # Data2Vec-Text base model
Pretrained model on English language using the *data2vec* objective. It was introduced in
[this paper](https://arxiv.org/abs/2202.03555) and first released in
[this repository](https://github.com/pytorch/fairseq/tree/main/examples/data2vec). This model is case-sensitive: it
makes a differenc... | null | [
"mit"
] | [
"bookcorpus",
"wikipedia"
] | [
"en"
] | null | null | null | [
"Data2VecTextModel",
"AutoModel",
"data2vec-text"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
6798b19d22b334a8377b7f90 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | open-thoughts/OpenThinker-7B | open-thoughts | {
"models": [
{
"_id": "66e81cbcd683a3f4e5291bbf",
"id": "Qwen/Qwen2.5-7B-Instruct"
}
],
"relation": "finetune"
} | 1,134 | 112,993 | False | 2025-01-28T10:29:49Z | 2025-06-05T16:18:51Z | transformers | 136 | 0 | [{"name": "OpenThinker-7B", "results": []}] | text-generation | {"parameters": {"BF16": 7615616512}, "total": 7615616512} | [
".gitattributes",
"README.md",
"added_tokens.json",
"all_results.json",
"config.json",
"configs.yaml",
"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",
"mode... | 4ba9dee9b7e6e4796c6bccf6e15c2f5b60843e1e | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"dataset:open-thoughts/open-thoughts-114k",
"arxiv:2506.04178",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:apac... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Aliba... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-7B-Instruct", "datasets": ["open-thoughts/open-thoughts-114k"], "eval_results": [], "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "OpenThinker-7B", "pipeline_tag": null, "tags": ["llama-f... | <p align="center">
<img src="https://huggingface.co/datasets/open-thoughts/open-thoughts-114k/resolve/main/open_thoughts.png" width="50%">
</p>
> [!NOTE]
> We have released a paper for OpenThoughts! See our paper [here](https://arxiv.org/abs/2506.04178).
# OpenThinker-7B
This model is a fine-tuned version of [Qw... | null | [
"apache-2.0"
] | [
"open-thoughts/open-thoughts-114k"
] | null | 7,615,616,512 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68b1a8464e972717522f60bb | a5eb961d82253050 | 6117be8f6e9dfaa6 | 151,679 | BPE | 151,387 | true | true | true | true | 36 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 939 | OpenGVLab/InternVL3_5-1B-HF | OpenGVLab | {
"models": [
{
"_id": "68ac9193f8ae7902de501e35",
"id": "OpenGVLab/InternVL3_5-1B-MPO"
}
],
"relation": "finetune"
} | 9,779 | 171,269 | False | 2025-08-29T13:16:54Z | 2025-09-08T09:51:06Z | transformers | 6 | 0 | null | image-text-to-text | {"parameters": {"BF16": 1060897792}, "total": 1060897792} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"examples/image1.jpg",
"examples/image2.jpg",
"examples/red-panda.mp4",
"generation_config.json",
"merges.txt",
"model.safetensors",
"preprocessor_config.json",
"processor_config.json",
"special_token... | 9191dbccf312b537016f041b25d61c72e7c5c9f3 | [
"transformers",
"safetensors",
"internvl",
"image-text-to-text",
"custom_code",
"conversational",
"multilingual",
"dataset:OpenGVLab/MMPR-v1.2",
"dataset:OpenGVLab/MMPR-Tiny",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.10442",
"arxiv:2504.10479",
"arxiv:2508.... | null | {"architectures": ["InternVLForConditionalGeneration"], "model_type": "internvl", "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null}, "chat_template_jinja": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n'}}{% if message['content'] ... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["OpenGVLab/InternVL3_5-1B-MPO"], "datasets": ["OpenGVLab/MMPR-v1.2", "OpenGVLab/MMPR-Tiny"], "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "imag... | # InternVL3_5-1B
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggingface.co/pap... | null | [
"apache-2.0"
] | [
"OpenGVLab/MMPR-v1.2",
"OpenGVLab/MMPR-Tiny"
] | [
"multilingual"
] | 1,060,897,792 | null | null | [
"internvl",
"InternVLForConditionalGeneration",
"AutoModelForImageTextToText"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
621ffdc136468d709f17872d | d82c716f01e57f52 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 62 | ainize/bart-base-cnn | ainize | null | 127 | 104,859 | False | 2022-03-02T23:29:05Z | 2021-06-21T09:52:44Z | transformers | 15 | 0 | null | summarization | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | b90bc9a7c93de6449a8c531ed5f957d84649b99a | [
"transformers",
"pytorch",
"bart",
"feature-extraction",
"summarization",
"en",
"dataset:cnn_dailymail",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BartModel", "BartForConditionalGeneration", "BartForSequenceClassification"], "model_type": "bart", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["cnn_dailymail"], "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": ["summarization", "bart"]} | # BART base model fine-tuned on CNN Dailymail
- This model is a [bart-base model](https://huggingface.co/facebook/bart-base) fine-tuned on the [CNN/Dailymail summarization dataset](https://huggingface.co/datasets/cnn_dailymail) using [Ainize Teachable-NLP](https://ainize.ai/teachable-nlp).
The Bart model was proposed... | null | [
"apache-2.0"
] | [
"cnn_dailymail"
] | [
"en"
] | null | null | null | [
"AutoModel",
"BartForConditionalGeneration",
"BartModel",
"BartForSequenceClassification",
"bart"
] | [
"summarization",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"text",
"embeddings"
] |
64273e9966821dcb668a9caa | fa3eb8b5ab2b6741 | 0bb73d739c8c3372 | 31,102 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 753 | nickprock/bert-italian-finetuned-ner | nickprock | {
"models": [
{
"_id": "621ffdc136468d709f17a49a",
"id": "dbmdz/bert-base-italian-cased"
}
],
"relation": "finetune"
} | 82 | 103,209 | False | 2023-03-31T20:12:09Z | 2023-09-12T07:25:47Z | transformers | 8 | 0 | [{"name": "bert-italian-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "wiki_neural", "type": "wiki_neural", "config": "it", "split": "validation", "args": "it"}, "metrics": [{"type": "precision", "value": 0.9438064759036144, "name": "Precision... | token-classification | {"parameters": {"I64": 512, "F32": 109362465}, "total": 109362977} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | e231fd727f9b4d242fe1a0ab204ad4e22f8aec56 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"it",
"dataset:tner/wikiann",
"base_model:dbmdz/bert-base-italian-cased",
"base_model:finetune:dbmdz/bert-base-italian-cased",
"license:mit",
"model-index",
"endpoints_compatible",
"region:u... | 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": "dbmdz/bert-base-italian-cased", "datasets": ["tner/wikiann"], "language": ["it"], "license": "mit", "metrics": ["precision", "recall", "f1", "accuracy"], "tags": ["generated_from_trainer"], "widget": [{"text": "Ciao, sono Giacomo. Vivo a Milano e lavoro da Armani. ", "example_title": "Example 1"}, {"tex... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-italian-finetuned-ner
This model is a fine-tuned version of [dbmdz/bert-base-italian-cased](https://huggingface.co/dbmdz/ber... | null | [
"mit"
] | [
"tner/wikiann"
] | [
"it"
] | 109,362,977 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6893ab4828f719381f665d40 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | unsloth/Qwen3-4B-Instruct-2507 | unsloth | {
"models": [
{
"_id": "6891e3bb084ce75acffb033d",
"id": "Qwen/Qwen3-4B-Instruct-2507"
}
],
"relation": "finetune"
} | 38,571 | 420,153 | False | 2025-08-06T19:21:44Z | 2025-08-06T21:35:26Z | transformers | 25 | 0 | null | text-generation | null | [
".gitattributes",
"LICENSE",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
... | 992063681dc2f7de4ee976110199552935cad284 | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"unsloth",
"conversational",
"arxiv:2505.09388",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|vision_pad|>", "unk_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].c... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen3-4B-Instruct-2507"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_... | <div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
<div style="display: flex; gap: 5px; align-items: center; ">
<a href="https://github.com/u... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507/blob/main/LICENSE"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17ee55 | 71140a663949f258 | 8a01c02d4d0a401c | 119,547 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 9 | philschmid/distilbert-base-multilingual-cased-sentiment | philschmid | null | 2,959 | 115,500 | False | 2022-03-02T23:29:05Z | 2022-01-24T12:14:53Z | transformers | 2 | 0 | [{"name": "distilbert-base-multilingual-cased-sentiment", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "amazon_reviews_multi", "type": "amazon_reviews_multi", "args": "all_languages"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value": 0.7648, "veri... | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"logs/1643020135.9116778/events.out.tfevents.1643020135.algo-1.507.1",
"logs/events.out.tfevents.1643020135.algo-1.507.0",
"logs/events.out.tfevents.1643026480.algo-1.507.2",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json... | b45a713783e49ac09c94dfda4bff847f4ad771c5 | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:amazon_reviews_multi",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["amazon_reviews_multi"], "license": "apache-2.0", "metrics": ["accuracy", "f1"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-multilingual-cased-sentiment", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "amazon_rev... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-multilingual-cased-sentiment
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://h... | null | [
"apache-2.0"
] | [
"amazon_reviews_multi"
] | null | null | null | [
"accuracy",
"f1"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6597dee85ddc4d0123c6085d | c67ed9877293591c | 7c4c85b636f4813b | 64,000 | BPE | 110,029 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 934 | cloudyu/Mixtral_34Bx2_MoE_60B | cloudyu | {
"models": [
{
"_id": "6566ff6932a48203e7f27cbc",
"id": "SUSTech/SUS-Chat-34B"
}
],
"relation": "finetune"
} | 7,992 | 142,711 | False | 2024-01-05T10:50:16Z | 2026-01-06T13:26:39Z | transformers | 114 | 0 | [{"name": "Mixtral_34Bx2_MoE_60B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "HuggingFaceH4/ifeval", "args": {"num_few_shot": 0}}, "metrics": [{"type": "inst_level_strict_acc and prompt_level_strict_acc", "value": 45.38, "name": "strict a... | text-generation | {"parameters": {"BF16": 60813892608}, "total": 60813892608} | [
".gitattributes",
"README.md",
"config.json",
"model-00001-of-00013.safetensors",
"model-00002-of-00013.safetensors",
"model-00003-of-00013.safetensors",
"model-00004-of-00013.safetensors",
"model-00005-of-00013.safetensors",
"model-00006-of-00013.safetensors",
"model-00007-of-00013.safetensors",
... | 2af346d4e212738941dada73082c2164bef4e00f | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"yi",
"moe",
"base_model:SUSTech/SUS-Chat-34B",
"base_model:finetune:SUSTech/SUS-Chat-34B",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<s>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["jondurbin/bagel-dpo-34b-v0.2", "SUSTech/SUS-Chat-34B"], "license": "apache-2.0", "tags": ["yi", "moe"], "model-index": [{"name": "Mixtral_34Bx2_MoE_60B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "HuggingFaceH4/ifeval", "... | # Mixtral MOE 2x34B
* [One of Best Model reviewed by reddit community](https://www.reddit.com/r/LocalLLaMA/comments/1916896/llm_comparisontest_confirm_leaderboard_big_news/)
* [Another review by reddit community](https://www.reddit.com/r/LocalLLaMA/comments/191mvlp/i_have_tried_mixtral_34bx2_moe_also_named_yi/)
Hig... | null | [
"apache-2.0"
] | null | null | 60,813,892,608 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1802e7 | 08d5e624483310cd | f87d7bfce4fd9617 | 30,000 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Replace",
"Replace",
"NFKD",
"StripAccents",
"Lowercase",
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 132 | sentence-transformers/paraphrase-albert-base-v2 | sentence-transformers | null | 131 | 103,735 | False | 2022-03-02T23:29:05Z | 2025-03-06T13:26:23Z | sentence-transformers | 5 | 0 | null | sentence-similarity | {"parameters": {"I64": 512, "F32": 11683584}, "total": 11684096} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"onnx/model.onnx",
"onnx/model_O1.onnx",
"onnx/model_O2.onnx",
"onnx/model_O3.onnx",
"onnx/model_O4.onnx",
"onnx/model_qint8_arm64.onnx",
"onnx/m... | 76bfe56d0951c7e7ca5211e8f342552f0ff560e8 | [
"sentence-transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"openvino",
"albert",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["AlbertModel"], "model_type": "albert", "tokenizer_config": {"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "<pad>", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "normalized": tru... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "sentence-transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction",... | # sentence-transformers/paraphrase-albert-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | null | [
"apache-2.0"
] | null | null | 11,684,096 | null | null | [
"AlbertModel",
"albert",
"AutoModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
65b5ab9cca3eb32979560a16 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | yunconglong/MoE_13B_DPO | yunconglong | null | 8,494 | 144,054 | False | 2024-01-28T01:19:24Z | 2024-01-28T06:49:29Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"BF16": 12879138816}, "total": 12879138816} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00006.safetensors",
"model-00002-of-00006.safetensors",
"model-00003-of-00006.safetensors",
"model-00004-of-00006.safetensors",
"model-00005-of-00006.safetensors",
"model-00006-of-00006.safetensors",
"model.s... | d8d6a47f877fee3e638a158c2bd637c0013ed4e4 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"DPO",
"RL-TUNED",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<s>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["moe", "DPO", "RL-TUNED"]} | * [DPO Trainer](https://huggingface.co/docs/trl/main/en/dpo_trainer) with dataset Intel/orca_dpo_pairs to improve [yunconglong/Truthful_DPO_TomGrc_FusionNet_7Bx2_MoE_13B]
```
DPO Trainer
TRL supports the DPO Trainer for training language models from preference data, as described in the paper Direct Preference Optimi... | null | [
"other"
] | null | null | 12,879,138,816 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
666836763cb8e1be3d260860 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | vicgalle/Configurable-Mistral-7B | vicgalle | null | 8,343 | 143,275 | False | 2024-06-11T11:35:18Z | 2024-06-11T11:42:29Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F16": 7241732096}, "total": 7241732096} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 6943dc17a4ba8160f3bbc050638c548bf9dd0c55 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"dataset:vicgalle/configurable-system-prompt-multitask",
"arxiv:1910.09700",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...'... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["vicgalle/configurable-system-prompt-multitask"], "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated... | null | [
"apache-2.0"
] | [
"vicgalle/configurable-system-prompt-multitask"
] | null | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
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"text"
] | [
"text"
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65af768e3e82498d4c64d581 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | uukuguy/speechless-zephyr-code-functionary-7b | uukuguy | null | 8,836 | 145,086 | False | 2024-01-23T08:19:26Z | 2024-01-25T07:15:51Z | transformers | 5 | 0 | null | text-generation | {"parameters": {"F32": 262144000, "BF16": 6979588096}, "total": 7241732096} | [
".gitattributes",
"GGUF/speechless-zephyr-code-functionary-7b.Q4_K_M.gguf",
"GGUF/speechless-zephyr-code-functionary-7b.Q5_K_M.gguf",
"GGUF/speechless-zephyr-code-functionary-7b.Q8_0.gguf",
"README.md",
"config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.saf... | d66fc775ece679966e352195c42444e9c70af7fa | [
"transformers",
"safetensors",
"gguf",
"mistral",
"text-generation",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | {"total": 7241732096, "architecture": "llama", "context_length": 32768, "bos_token": "<s>", "eos_token": "</s>"} | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | <p><h1> speechless-zephyr-code-functionary-7b </h1></p>
[4,5,8-bit GGUF models for CPU+GPU inference](https://huggingface.co/uukuguy/speechless-zephyr-code-functionary-7b/tree/main/GGUF)
This model is the one of the moloras (Mixture-of-Multi-LoRAs) experiments.
Extract LoRA modules from below models (all based Mistr... | null | [
"apache-2.0"
] | null | [
"en"
] | 7,241,732,096 | 7,241,732,096 | null | [
"AutoModelForCausalLM",
"llama",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65ccda15fd5f628b15b736e5 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | unsloth/tinyllama-chat | unsloth | null | 9,366 | 144,763 | False | 2024-02-14T15:19:49Z | 2024-09-03T03:42:53Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"BF16": 1100048384}, "total": 1100048384} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | e25260eb1960e3670a1e029418cc4ea69ffea6d0 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"unsloth",
"tinyllama",
"chat",
"conversational",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content']... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "transformers", "tinyllama", "chat"]} | # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%... | null | [
"apache-2.0"
] | null | [
"en"
] | 1,100,048,384 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6676f58c585f2bf57054d2ec | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | arcee-ai/Arcee-Spark | arcee-ai | null | 407 | 104,145 | False | 2024-06-22T16:02:20Z | 2024-07-22T12:56:06Z | transformers | 86 | 0 | [{"name": "Arcee-Spark", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "HuggingFaceH4/ifeval", "args": {"num_few_shot": 0}}, "metrics": [{"type": "inst_level_strict_acc and prompt_level_strict_acc", "value": 56.21, "name": "strict accuracy", ... | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",
"model.safetensors.index.json",
"special_to... | 69bafc5fc790f3d663094fdc9220a4b7ca0ba654 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"de",
"ar",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"language": ["en", "de", "ar"], "license": "apache-2.0", "model-index": [{"name": "Arcee-Spark", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "HuggingFaceH4/ifeval", "args": {"num_few_shot": 0}}, "metrics": [{"type": "inst_level_strict_acc ... | <div align="center">
<img src="https://i.ibb.co/80ssNWS/o-Vdk-Qx-ARNmzr-Pi1h-Efj-SA.webp" alt="Arcee Spark" style="border-radius: 10px; box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.2), 0 6px 20px 0 rgba(0, 0, 0, 0.19); max-width: 100%; height: auto;">
</div>
# Arcee Spark
Arcee Spark is a powerful 7B parameter language ... | null | [
"apache-2.0"
] | null | [
"en",
"de",
"ar"
] | null | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
683876fdd011eaeee3cf9ada | 484da11a3d71bbf8 | a7b4167b9e661fe0 | 151,671 | BPE | 151,387 | true | true | true | true | 28 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 847 | unsloth/DeepSeek-R1-0528-Qwen3-8B-unsloth-bnb-4bit | unsloth | {
"models": [
{
"_id": "68384003444a0e00ec791df0",
"id": "deepseek-ai/DeepSeek-R1-0528-Qwen3-8B"
}
],
"relation": "quantized"
} | 6,016 | 137,103 | False | 2025-05-29T15:02:21Z | 2025-06-10T05:35:05Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"F32": 427728, "BF16": 2167714816, "U8": 6211316084}, "total": 8379458628} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | c5b5906bbd28e695973375f987371d71b35074a1 | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"unsloth",
"deepseek",
"qwen",
"conversational",
"arxiv:2501.12948",
"base_model:deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
"license:mit",
"text-generation-inference",
"end... | null | {"architectures": ["Qwen3ForCausalLM"], "model_type": "qwen3", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<\uff5cbegin\u2581of\u2581sentence\uff5c>", "eos_token": "<\uff5cend\u2581of\u2581sentence\uff5c>", "pad_token": "<|visi... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["deepseek-ai/DeepSeek-R1-0528-Qwen3-8B"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["unsloth", "deepseek", "qwen"]} | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>Learn how to run DeepSeek-R1-0528 correctly - <a href="https://docs.unsloth.ai/basics/deepseek-r1-0528">Read our Guide</a>.</strong>
</p>
<p style="margin-bottom: 0;">
<em>See <a href="https://huggingface.co/collections/unsloth/deepseek-r1-all-ver... | null | [
"mit"
] | null | null | 8,379,458,628 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1799d2 | 3d2faa8ffdfba070 | 5f9f736c7dc6fbfa | 28,996 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 446 | bhadresh-savani/distilbert-base-uncased-sentiment-sst2 | bhadresh-savani | null | 77 | 102,390 | False | 2022-03-02T23:29:05Z | 2022-06-15T11:48:33Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"convert_flax_to_pytorch.py",
"convert_pytorch_to_flax.py",
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"flax_model.msgpack",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | b91676624bfec8bb96d31c4d0f1b13a491ebe65c | [
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"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["sst2"], "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # distilbert-base-uncased-sentiment-sst2
This model will be able to identify positivity or negativity present in the sentence
## Dataset:
The Stanford Sentiment Treebank from GLUE
## Results:
```
***** eval metrics *****
epoch = 3.0
eval_accuracy = 0.9094
eval_loss ... | null | [
"apache-2.0"
] | [
"sst2"
] | [
"en"
] | null | null | null | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc136468d709f17f00f | 32583745c0717077 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 940 | pritamdeka/S-Bluebert-snli-multinli-stsb | pritamdeka | null | 97 | 102,436 | False | 2022-03-02T23:29:05Z | 2022-09-21T18:58:03Z | sentence-transformers | 7 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"eval/similarity_evaluation_sts-dev_results.csv",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"similarity_evaluation_sts-test_results.csv",
"special_tokens_map.json",... | 8d4b33f320e308f7c86ac061a4880f1a9422ba7c | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "tr... | # pritamdeka/S-Bluebert-snli-multinli-stsb
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)
Using th... | null | null | null | null | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
65c98b76a1bcb439170f3c4f | dd3bf0749afb5b4c | ea6e051246d01ec3 | 36,608 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 941 | OpenBuddy/openbuddy-mixtral-7bx8-v18.1-32k | OpenBuddy | null | 125 | 102,465 | False | 2024-02-12T03:07:34Z | 2024-03-04T16:58:22Z | transformers | 13 | 0 | [{"name": "openbuddy-mixtral-7bx8-v18.1-32k", "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": 67.6... | text-generation | {"parameters": {"BF16": 46740541440}, "total": 46740541440} | [
".gitattributes",
"Evaluation.txt",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00019.safetensors",
"model-00002-of-00019.safetensors",
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"model-00004-of-00019.safetensors",
"model-00005-of-00019.safetensors",
"model-00006-of-00019.safe... | 98596b6731058cc9cca85f3b8ac9077342cb60ae | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"conversational",
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstr... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"language": ["zh", "en", "fr", "de", "ja", "ko", "it", "ru"], "library_name": "transformers", "license": "apache-2.0", "pipeline_tag": "text-generation", "inference": false, "model-index": [{"name": "openbuddy-mixtral-7bx8-v18.1-32k", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "datase... | # OpenBuddy - Open Multilingual Chatbot
GitHub and Usage Guide: [https://github.com/OpenBuddy/OpenBuddy](https://github.com/OpenBuddy/OpenBuddy)
Website and Demo: [https://openbuddy.ai](https://openbuddy.ai)
Evaluation result of this model: [Evaluation.txt](Evaluation.txt)
![Demo](https://raw.githubusercontent.com/... | null | [
"apache-2.0"
] | null | [
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru"
] | 46,740,541,440 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64c5e9c237333ccfef092a4c | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | vishnun/codenlbert-sm | vishnun | null | 5,411 | 123,330 | False | 2023-07-30T04:40:34Z | 2023-08-03T18:01:06Z | transformers | 0 | 0 | null | text-classification | {"parameters": {"I64": 512, "F32": 28764674}, "total": 28765186} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | caa3d167fd262c76c7da23cd72c1d24cfdcafd0f | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"nlp",
"code",
"classification",
"en",
"dataset:vishnun/CodevsNL",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["vishnun/CodevsNL"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["nlp", "code", "classification"]} | ## PreFace
Code vs Natural language classification using bert-small from prajwall, below are the metrics achieved
## Training Metrics
| Epoch | Training Loss | Validation Loss | Accuracy | |
|------:|--------------:|----------------:|---------:|---|
| 1 | 0.022500 | 0.012705 | 0.997203 | |
| 2... | null | null | [
"vishnun/CodevsNL"
] | [
"en"
] | 28,765,186 | null | [
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
679c2762564c63b9e3c4259f | af8f34566d80cb0d | 478e8ebb5343b763 | 99,574 | Unigram | null | true | false | true | true | 8 | Sequence | null | Sequence | [
"Replace",
"Replace"
] | null | [
"ByteFallback",
"Replace",
"Fuse",
"Replace"
] | 583 | llm-jp/llm-jp-3-7.2b-instruct3 | llm-jp | null | 426 | 117,515 | False | 2025-01-31T01:29:06Z | 2025-02-04T04:58:45Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"BF16": 7292063744}, "total": 7292063744} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | cdd4c7f3296fdc7785423a864bd9a86ce4c15915 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"en",
"ja",
"license:apache-2.0",
"text-generation-inference",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{bos_token}}{% for message in messages %}{% if message['role'] == 'user' %}{{ '\\n\\n### \u6307\u793a:\\n' + message['content'] }}{% elif message['role'] == 'system' %}{{ '\u4ee5\u4e0b\u306f\u3001\... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "ja"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "programming_language": ["C", "C++", "C#", "Go... | # llm-jp-3-7.2b-instruct3
LLM-jp-3 is the series of large language models developed by the [Research and Development Center for Large Language Models](https://llmc.nii.ac.jp/) at the [National Institute of Informatics](https://www.nii.ac.jp/en/).
This repository provides **llm-jp-3-7.2b-instruct3** model.
For an over... | null | [
"apache-2.0"
] | null | [
"en",
"ja"
] | 7,292,063,744 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6517e20fb4bfc5d912df2158 | 63f54837f1a489f8 | 07ae163ec241d8d4 | 52,000 | BPE | 51,740 | true | true | true | true | 4 | NFKC | ByteLevel | ByteLevel | [
"NFKC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 942 | FINDA-FIT/llama-r | FINDA-FIT | null | 804 | 106,202 | False | 2023-09-30T08:53:35Z | 2023-09-30T09:11:54Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"config.json",
"generation_config.json",
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"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 6bdde9a227da60c2db803024d5b2e3a53a41cf0b | [
"transformers",
"pytorch",
"llama",
"text-generation",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|sep|>", "eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65c27bfd71829ecd88ebc0c7 | 925bc1b18c2f0c84 | 963b5f887d151645 | 49,154 | BPE | 48,891 | false | true | false | true | 21 | null | Sequence | ByteLevel | null | [
"Digits",
"ByteLevel"
] | [
"ByteLevel"
] | 357 | codesage/codesage-small | codesage | null | 241 | 102,565 | False | 2024-02-06T18:35:41Z | 2024-12-28T22:14:47Z | transformers | 6 | 0 | null | null | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"added_tokens.json",
"config.json",
"config_codesage.py",
"generation_config.json",
"merges.txt",
"modeling_codesage.py",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenization_codes... | 4d2a4f3fa73a3c8a4dd59dba2712202f1f54e109 | [
"transformers",
"pytorch",
"custom_code",
"code",
"dataset:bigcode/the-stack-dedup",
"arxiv:2402.01935",
"arxiv:2305.06161",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["CodeSage"], "auto_map": {"AutoConfig": "config_codesage.CodeSageConfig", "AutoTokenizer": "tokenization_codesage.CodeSageTokenizer", "AutoModel": "modeling_codesage.CodeSageModel", "AutoModelForMaskedLM": "modeling_codesage.CodeSageForMaskedLM", "AutoModelForSequenceClassification": "modeling_codesa... | {
"auto_model": "CodeSage",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": ["bigcode/the-stack-dedup"], "eval_results": null, "language": ["code"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | ## CodeSage-Small
### Updates
* [12/2024] <span style="color:blue">We are excited to announce the release of the CodeSage V2 model family with largely improved performance and flexible embedding dimensions!</span> Please check out our [models](https://huggingface.co/codesage) and [blogpost](https://code-representation... | null | [
"apache-2.0"
] | [
"bigcode/the-stack-dedup"
] | [
"code"
] | null | null | null | [
"CodeSage"
] | [
null
] | null | null | null |
659421c3f7291078f975388e | 9ac8007769430953 | 9c538a252770db2d | 64,002 | BPE | 110,029 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 943 | Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp | Weyaxi | null | 8,587 | 144,054 | False | 2024-01-02T14:46:27Z | 2024-01-19T14:27:24Z | transformers | 1 | 0 | [{"name": "Nous-Hermes-2-SUS-Chat-34B-Slerp", "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": 66.7... | text-generation | {"parameters": {"BF16": 34388945920}, "total": 34388945920} | [
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"added_tokens.json",
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"model-00003-of-00008.safetensors",
"model-00004-of-00008.safetensors",
"model-00005-of-00008.safetensors",
... | 4876da6fad938faabbd670f8fb3d02eddf3b5d02 | [
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"llama",
"text-generation",
"merge",
"license:other",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|startoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<unk>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"license": "other", "license_name": "yi-34b", "license_link": "https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE", "tags": ["merge"], "model-index": [{"name": "Nous-Hermes-2-SUS-Chat-34B-Slerp", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challeng... | 
# Nous-Hermes-2-SUS-Chat-34B-Slerp
This is the model for Nous-Hermes-2-SUS-Chat-34B-Slerp. I used [mergekit](https://github.com/cg123/mergekit) to merge models.
# Prompt Templates
You can use these... | null | [
"other",
"yi-34b",
"https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE"
] | null | null | 34,388,945,920 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
656114396573ea070818e800 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | migtissera/Tess-XS-v1-3-yarn-128K | migtissera | null | 2,852 | 117,964 | False | 2023-11-24T21:23:05Z | 2023-12-04T16:54:03Z | transformers | 13 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_mistral.py",
"modeling_mistral_yarn.py",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 72d393d13f1bd26442e59993c57840b91ff6f6fc | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"custom_code",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "auto_map": {"AutoConfig": "configuration_mistral.MistralConfig", "AutoModelForCausalLM": "modeling_mistral_yarn.MistralForCausalLM"}, "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "</s>", "unk_token": "<unk>", "use_default_... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Note:
This version is the stable release. The issues that were present in versions 1.0, 1.1 and 1.2 all have been rectified. Thank you for your patience while R&D was conducted. Enjoy!
This model have been tested on context length up to 16K. Model produced slight repetition around 16K context length. I recommend te... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65ba3b7932dd6c222f2554ae | 09574be15ef6a4ca | 081b543d8f95004e | 32,002 | BPE | 58,980 | true | false | true | true | 5 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 625 | AIJUUD/juud-Mistral-7B | AIJUUD | null | 122 | 101,784 | False | 2024-01-31T12:22:17Z | 2024-02-03T22:48:16Z | transformers | 4 | 0 | null | text-generation | {"parameters": {"F16": 7241748480}, "total": 7241748480} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model... | 76058e6eb5bc547cb2b88e7eb59cec89c0dc302c | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% end... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Model Card for Model ID
Welcome To BNK AI.
You now are seeing Initiative status of Huge AI Team like mackintosh Garage company
Though beginning seems humble future will be prosperous!
If you have a question, feel free to
contact to bnkaiteam@gmail.com
![image/png](https://cdn-uploads.huggingface.co/production/up... | null | [
"apache-2.0"
] | null | null | 7,241,748,480 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
666ddb14eeca3ee660f5771d | f5e7f943c396c76b | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 52 | Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO | Danielbrdz | null | 8,318 | 141,966 | False | 2024-06-15T18:19:00Z | 2024-06-15T19:48:23Z | transformers | 5 | 0 | null | text-generation | {"parameters": {"F16": 13960238080}, "total": 13960238080} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00006.safetensors",
"model-00002-of-00006.safetensors",
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"model-00004-of-00006.safetensors",
"model-00005-of-00006.safetensors",
"model-00006-of-00006.safetensors",
"model.s... | b749dbcb19901b8fd0e9f38c923a24533569f895 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"ORPO",
"conversational",
"en",
"dataset:mlabonne/orpo-dpo-mix-40k",
"license:mit",
"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 %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["mlabonne/orpo-dpo-mix-40k"], "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": ["ORPO"]} | Barcenas-14b-Phi-3-medium-ORPO
Model trained with the innovative ORPO method, based on the robust VAGOsolutions/SauerkrautLM-Phi-3-medium.
The model was trained with the dataset: mlabonne/orpo-dpo-mix-40k, which combines diverse data sources to enhance conversational capabilities and contextual understanding.
Made w... | null | [
"mit"
] | [
"mlabonne/orpo-dpo-mix-40k"
] | [
"en"
] | 13,960,238,080 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6699cff48f2dbc203fa4577d | 595f48517e0303f3 | 12ebeebff692ebb1 | 131,072 | BPE | 269,443 | false | true | true | true | 1,000 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 497 | ModelCloud/Mistral-Nemo-Instruct-2407-gptq-4bit | ModelCloud | null | 37 | 101,743 | False | 2024-07-19T02:31:16Z | 2024-07-23T18:36:13Z | transformers | 5 | 0 | null | text-generation | {"parameters": {"I32": 10905190400, "BF16": 1342592000}, "total": 12247782400} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"quantize_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 3feee008f16014f4c21d50b0e95b41cd17d6c8d5 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mistral-nemo",
"gptq",
"4bit",
"int4",
"gptqmodel",
"modelcloud",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "tokenizer_config": {"bos_token": "<s>", "chat_template": "{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content'] %}\n {%- set loop_messages = message... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["mistral-nemo", "gptq", "4bit", "int4", "gptqmodel", "modelcloud"]} | This model has been quantized using [GPTQModel](https://github.com/ModelCloud/GPTQModel).
- **bits**: 4
- **group_size**: 128
- **desc_act**: true
- **static_groups**: false
- **sym**: true
- **lm_head**: false
- **damp_percent**: 0.01
- **true_sequential**: true
- **model_name_or_path**: ""
- **model_file_base_name**... | null | null | null | null | 12,247,782,400 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68c54028edb3834963d798e2 | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | unsloth/Qwen3-Next-80B-A3B-Instruct-bnb-4bit | unsloth | {
"models": [
{
"_id": "68c04a8865953b21d7f88ec6",
"id": "Qwen/Qwen3-Next-80B-A3B-Instruct"
}
],
"relation": "quantized"
} | 24,565 | 414,314 | False | 2025-09-13T09:58:00Z | 2025-09-13T09:58:35Z | transformers | 27 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00009.safetensors",
"model-00002-of-00009.safetensors",
"model-00003-of-00009.safetensors",
"model-00004-of-00009.safetensors",
"model-00005-of-0000... | 636c94e8dc5f2fb1b675f87190d2aba39e4f03c6 | [
"transformers",
"safetensors",
"qwen3_next",
"text-generation",
"unsloth",
"conversational",
"arxiv:2309.00071",
"arxiv:2404.06654",
"arxiv:2505.09388",
"arxiv:2501.15383",
"base_model:Qwen/Qwen3-Next-80B-A3B-Instruct",
"base_model:quantized:Qwen/Qwen3-Next-80B-A3B-Instruct",
"license:apache... | null | {"architectures": ["Qwen3NextForCausalLM"], "model_type": "qwen3_next", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|vision_pad|>", "unk_token": null, "chat_template": "{%- if tool... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["Qwen/Qwen3-Next-80B-A3B-Instruct"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct/blob/main/LICENSE", "metrics": null, "model_name": null, ... | <div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
<div style="display: flex; gap: 5px; align-items: center; ">
<a href="https://github.com/u... | null | [
"apache-2.0",
"https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct/blob/main/LICENSE"
] | null | null | null | null | null | [
"qwen3_next",
"Qwen3NextForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1750e4 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | Davlan/xlm-roberta-base-wikiann-ner | Davlan | null | 2,249 | 106,965 | False | 2022-03-02T23:29:04Z | 2023-06-25T07:32:38Z | transformers | 6 | 0 | null | token-classification | {"parameters": {"I64": 514, "F32": 277459977}, "total": 277460491} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | 642b9a14e71df124c43c67e47703a91341576dfb | [
"transformers",
"pytorch",
"tf",
"safetensors",
"xlm-roberta",
"token-classification",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["XLMRobertaForTokenClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": fals... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | null | # xlm-roberta-base-wikiann-ner
## Model description
**xlm-roberta-base-wikiann-ner** is the first **Named Entity Recognition** model for 20 languages (Arabic, Assamese, Bengali, Catalan, English, Spanish, Basque, French, Gujarati, Hindi, Indonesia, Igbo, Marathi, Punjabi, Portugues and Swahili, Urdu, Vietnamese, Yor... | null | null | null | null | 277,460,491 | null | null | [
"XLMRobertaForTokenClassification",
"AutoModelForTokenClassification",
"xlm-roberta"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
67fb1c9d0c3e0fda76298581 | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | TIGER-Lab/VL-Rethinker-7B | TIGER-Lab | {
"models": [
{
"_id": "6795ffcd88cd7c0294702a72",
"id": "Qwen/Qwen2.5-VL-7B-Instruct"
}
],
"relation": "finetune"
} | 299 | 104,780 | False | 2025-04-13T02:08:29Z | 2025-05-05T17:47:01Z | transformers | 14 | 0 | null | image-text-to-text | {"parameters": {"BF16": 8292166656}, "total": 8292166656} | [
".gitattributes",
"README.md",
"added_tokens.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.safetensors.in... | 5439d11fc9fa1474ab015104e6604223f165ccf5 | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"multimodal",
"conversational",
"en",
"arxiv:2504.08837",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",... | null | {"architectures": ["Qwen2_5_VLForConditionalGeneration"], "model_type": "qwen2_5_vl", "processor_config": {"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a h... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["Qwen/Qwen2.5-VL-7B-Instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": ["transformers", "multimodal... | # VL-Rethinker-7B
**🚀 News:** <u>We release our meticulously curated collection of RL training queries for multimodal reasoning: [ViRL39K](https://huggingface.co/datasets/TIGER-Lab/ViRL39K).</u>
**VL-Rethinker-7B** achieves SoTA results on various multimodal reasoning benchmarks.
It is trained using the **GRPO-SSR ... | null | [
"apache-2.0"
] | null | [
"en"
] | 8,292,166,656 | null | null | [
"qwen2_5_vl",
"AutoModelForImageTextToText",
"Qwen2_5_VLForConditionalGeneration"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
65d21973c4d2b2e402d2c287 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | abacusai/Smaug-Mixtral-v0.1 | abacusai | null | 8,545 | 142,393 | False | 2024-02-18T14:51:31Z | 2024-02-21T19:13:07Z | transformers | 12 | 0 | null | text-generation | {"parameters": {"F32": 46702792704}, "total": 46702792704} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00039.safetensors",
"model-00002-of-00039.safetensors",
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"model-00004-of-00039.safetensors",
"model-00005-of-00039.safetensors",
"model-00006-of-00039.safetensors",
"model-0... | 98fdc8315906b0a8b9e7f24bad89914869fcfc20 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"finetune",
"conversational",
"arxiv:2402.13228",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...'... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["mixtral", "finetune"]} | ## Overview
This model is part of the Smaug series of finetuned models. This one based on https://huggingface.co/mistralai/Mixtral-8x7B-v0.1
We use a new fine-tuning technique, DPO-Positive (DPOP), and new pairwise preference versions of ARC, HellaSwag, and MetaMath (as well as other existing datasets).
We introduce... | null | [
"apache-2.0"
] | null | null | 46,702,792,704 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
649f51759d0d8fabee671394 | bfcaaa8fd0d4cee0 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 944 | yongsun-yoon/minilmv2-bertscore-distilled | yongsun-yoon | null | 2 | 101,009 | False | 2023-06-30T22:04:37Z | 2023-07-06T23:00:56Z | transformers | 0 | 0 | null | feature-extraction | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 3a68784dd2e143726a85e28adba942a226e48e67 | [
"transformers",
"pytorch",
"roberta",
"feature-extraction",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaModel"], "model_type": "roberta", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | null | This is a distilled BERTScore model.
Please read [this post](https://medium.com/@yongsun.yoon/bertscore-knowledge-distillation-42721b3508e2) for details.
```python
from bert_score import BERTScorer
texts1 = ['This is a text.']
texts2 = ['This is another text.']
scorer = BERTScorer(model_type='yongsun-yoon/minilmv2-b... | null | null | null | null | null | null | null | [
"roberta",
"AutoModel",
"RobertaModel"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
651ac0069e0f56bb7fb199c8 | 8a5ed303ac35025e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 945 | hyunseoki/ko-en-llama2-13b | hyunseoki | null | 782 | 105,307 | False | 2023-10-02T13:05:10Z | 2023-10-03T18:49:04Z | transformers | 27 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00003.bin",
"pytorch_model-00002-of-00003.bin",
"pytorch_model-00003-of-00003.bin",
"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.... | 2768cf6f955b65868ccbb20658e2cc444b2f3be9 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"ko",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ko"], "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | **Model Developers** HyunseokLee, TaeyoungKim - (kaist alinlab, omnious.ai)
**Input** Models input text only.
**Output** Models generate text only.
**Model Architecture**
ko-en-llama2-13b is an auto-regressive language model based on the LLaMA2 transformer architecture.
**Base Model**
Llama-2-13B
**Training Da... | null | null | null | [
"ko"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f1774fb | c124163b72739cca | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 162 | Shahm/t5-small-german | Shahm | null | 41 | 101,300 | False | 2022-03-02T23:29:05Z | 2023-08-29T13:26:02Z | transformers | 1 | 0 | [{"name": "t5-seven-epoch-base-german", "results": [{"task": {"name": "Summarization", "type": "summarization"}, "dataset": {"name": "mlsum de", "type": "mlsum", "args": "de"}, "metrics": [{"name": "Rouge1", "type": "rouge", "value": 42.3787, "verified": false}]}]}] | summarization | {"parameters": {"F32": 60492288}, "total": 60492288} | [
".gitattributes",
".gitignore",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"model.safetensors",
"pytorch_model.bin",
"runs/Dec24_22-16-55_5adbd5d9988b/1640384759.2212787/events.out.tfevents.1640384759.5adbd5d9988b.2555.1",
"runs/Dec24_22-16-55_5adbd5d9988b/events.out.tfev... | 9c8ef855975ce52b35e6f464234e4abdc8199140 | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"summarization",
"de",
"dataset:mlsum",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["mlsum"], "language": "de", "license": "apache-2.0", "metrics": ["rouge"], "tags": ["generated_from_trainer", "summarization"], "model-index": [{"name": "t5-seven-epoch-base-german", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "mlsum de", "type": "mlsum", "... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-seven-epoch-base-german
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the mlsum de data... | null | [
"apache-2.0"
] | [
"mlsum"
] | [
"de"
] | 60,492,288 | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65e7d6dfc7a0617cc712c5a5 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | abacusai/bigstral-12b-32k | abacusai | {
"models": [
{
"_id": "65770c3426ef61bbf101d4da",
"id": "mistralai/Mistral-7B-Instruct-v0.2"
}
],
"relation": "finetune"
} | 7,911 | 138,839 | False | 2024-03-06T02:37:19Z | 2024-09-09T14:56:57Z | transformers | 44 | 0 | [{"name": "bigstral-12b-32k", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "HuggingFaceH4/ifeval", "args": {"num_few_shot": 0}}, "metrics": [{"type": "inst_level_strict_acc and prompt_level_strict_acc", "value": 41.94, "name": "strict accura... | text-generation | {"parameters": {"F16": 12476420096}, "total": 12476420096} | [
".gitattributes",
"README.md",
"config.json",
"mergekit_config.yml",
"model-00001-of-00003.safetensors",
"model-00002-of-00003.safetensors",
"model-00003-of-00003.safetensors",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.jso... | cf85301bc4deed33852c292cc6d6ae8ff946c129 | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatib... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...'... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["mistralai/Mistral-7B-Instruct-v0.2"], "library_name": "transformers", "license": "apache-2.0", "tags": ["mergekit", "merge"], "model-index": [{"name": "bigstral-12b-32k", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "Hugging... | # bigstral-12b-32k
`ollama run ehartford/bigstral`
I reached for SOLAR but realized that its only 4k... Decided to make my own 32k version.
This is [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) with layers interleaved to create a larger 12b model.
This is a merge ... | null | [
"apache-2.0"
] | null | null | 12,476,420,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
632694b79f9d19bfd4f65856 | 2012b52fa41ec860 | db117e9883c4d0ab | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 113 | Gustavosta/MagicPrompt-Dalle | Gustavosta | null | 492 | 103,353 | False | 2022-09-18T03:47:03Z | 2023-03-17T21:38:43Z | transformers | 48 | 0 | null | text-generation | {"parameters": {"F32": 124439808, "U8": 12582912}, "total": 137022720} | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 9517172240a8b5a832e2399eaa0650f3b4539dd6 | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # MagicPrompt - Dall-E 2
This is a model from the MagicPrompt series of models, which are [GPT-2](https://huggingface.co/gpt2) models intended to generate prompt texts for imaging AIs, in this case: [Dall-E 2](https://openai.com/dall-e-2/).
## 🖼️ Here's an example:
<img src="https://files.catbox.moe/h10plz.png">
T... | null | [
"mit"
] | null | null | 137,022,720 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17a609 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 28 | deepset/xlm-roberta-base-squad2-distilled | deepset | null | 1,236 | 104,618 | False | 2022-03-02T23:29:05Z | 2024-09-26T10:51:58Z | transformers | 11 | 0 | null | question-answering | {"parameters": {"I64": 514, "F32": 277454594}, "total": 277455108} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | c1bbfe57bc3335c37960a48c5628ba26d7e9e3b7 | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"question-answering",
"exbert",
"multilingual",
"dataset:squad_v2",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaForQuestionAnswering"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false,... | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad_v2"], "eval_results": null, "language": "multilingual", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["exbert"], "thumbnail": "https://thumb.tildacdn.com/tild3433-3637-4830-... | # Multilingual XLM-RoBERTa base distilled for Extractive QA on various languages
- Haystack's distillation feature was used for training. deepset/xlm-roberta-large-squad2 was used as the teacher model.
## Overview
**Language model:** deepset/xlm-roberta-base-squad2-distilled
**Language:** Multilingual
**Downstrea... | null | [
"mit"
] | [
"squad_v2"
] | [
"multilingual"
] | 277,455,108 | null | null | [
"AutoModelForQuestionAnswering",
"XLMRobertaForQuestionAnswering",
"xlm-roberta"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
673f9329cbde13f56318e0fc | 7b66071fbb0d7bdc | 7d900c9c71170270 | 257,153 | BPE | 580,604 | true | true | true | true | 1,370 | Replace | Split | Sequence | [
"Replace"
] | [
"Split"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 171 | google/paligemma2-3b-pt-448 | google | null | 44,152 | 189,039 | manual | 2024-11-21T20:08:09Z | 2024-12-05T12:45:16Z | transformers | 46 | 0 | null | image-text-to-text | {"parameters": {"BF16": 3033127152}, "total": 3033127152} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"preprocessor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | bd60523c1ff2b0020c11e68affe65ef0b2379cab | [
"transformers",
"safetensors",
"paligemma",
"image-text-to-text",
"arxiv:2407.07726",
"arxiv:2408.00118",
"arxiv:2310.09199",
"arxiv:2303.15343",
"arxiv:1706.03762",
"arxiv:2010.11929",
"arxiv:2412.03555",
"arxiv:2209.06794",
"arxiv:2209.04372",
"arxiv:2103.01913",
"arxiv:1908.04913",
... | null | {"architectures": ["PaliGemmaForConditionalGeneration"], "model_type": "paligemma", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "image-text-to-text", "tags": null, "extra_gated_heading": "Access PaliGemma on Hugging Face... | null | null | [
"gemma"
] | null | null | 3,033,127,152 | null | null | [
"PaliGemmaForConditionalGeneration",
"AutoModelForImageTextToText",
"paligemma"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
64ab79facc73827ce6afe8c8 | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | PAIXAI/Astrid-1B | PAIXAI | null | 17 | 100,579 | False | 2023-07-10T03:24:42Z | 2023-08-21T22:54:02Z | transformers | 24 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"cfg.yaml",
"config.json",
"generation_config.json",
"h2oai_pipeline.py",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 3551b55e2c64fd30a10a041df05b890fef259405 | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"gpt",
"llm",
"large language model",
"PAIX.Cloud",
"en",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["gpt", "llm", "large language model", "PAIX.Cloud"], "inference": true, "thumb... | # Model Card
## Summary
This model, Astrid-1B, is a GPT-NeoX model for causal language modeling, designed to generate human-like text.
It's part of our mission to make AI technology accessible to everyone, focusing on personalization, data privacy, and transparent AI governance.
Trained in English, it's a versatile... | null | null | null | [
"en"
] | null | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
"GPTNeoXForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6841b5242313043afa857b43 | d9abafc9e84f6e37 | 298fb2136b26cee9 | 131,072 | BPE | 269,443 | false | true | true | true | 1,000 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 482 | nvidia/Nemotron-H-8B-Reasoning-128K | nvidia | null | 1,347 | 105,588 | False | 2025-06-05T15:17:56Z | 2025-07-11T16:34:34Z | transformers | 27 | 1 | null | text-generation | {"parameters": {"BF16": 8100852736}, "total": 8100852736} | [
".gitattributes",
"README.md",
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"configuration_nemotron_h.py",
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"model.safetensors.index.json",
"modeling_nemotro... | 2dcbcfd95b103843b6ad8e79690f34480ce5a5ae | [
"transformers",
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"conversational",
"en",
"arxiv:2504.03624",
"arxiv:2505.00949",
"license:other",
"endpoints_compatible",
"region:us"
] | null | {"tokenizer_config": {"bos_token": null, "chat_template": "{{ '<SPECIAL_10>System\n' }}{%- if messages and messages[0]['role'] == 'system' -%}{{ messages[0]['content'].strip() }}{%- endif -%}{% for message in (messages[1:] if messages[0]['role'] == 'system' else messages) %}{%- if message['role'] == 'user' -%}{{ '\n<SP... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "other", "license_name": "nvidia-internal-scientific-research-and-development-model-license", "license_link": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-internal-scientifi... | null | null | [
"other",
"nvidia-internal-scientific-research-and-development-model-license",
"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-internal-scientific-research-and-development-model-license/"
] | null | [
"en"
] | 8,100,852,736 | null | null | [
"AutoModel"
] | [
null,
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65d6361bdbfd082b5e4db6be | e2c43495aed6e9fb | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | false | true | true | 217 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 106 | unsloth/gemma-2b-it-bnb-4bit | unsloth | null | 3,783 | 116,294 | False | 2024-02-21T17:42:51Z | 2024-09-03T03:44:13Z | transformers | 20 | 0 | null | text-classification | {"parameters": {"F32": 155232, "BF16": 524363776, "U8": 2043783426}, "total": 2568302434} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | 3fbfee2e9ac98e9ac58890011d74b0367fe3ecc0 | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"unsloth",
"gemma-2b",
"bnb",
"text-classification",
"en",
"license:apache-2.0",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not sup... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": ["unsloth", "transformers", "gemma", "gemma-2b", "bnb"... | # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%... | null | [
"apache-2.0"
] | null | [
"en"
] | 2,568,302,434 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation",
"text-classification"
] | [
"text"
] | [
"text"
] | [
"text",
"logits"
] |
66397aba7256327c68940bca | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | failspy/llama-3-70B-Instruct-abliterated | failspy | null | 8,672 | 142,610 | False | 2024-05-07T00:50:02Z | 2024-05-07T15:36:53Z | transformers | 127 | 1 | null | text-generation | null | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00030.safetensors",
"model-00002-of-00030.safetensors",
"model-00003-of-00030.safetensors",
"model-00004-of-00030.safetensors",
"model-00005-of-00030.safetensors",
"model-00006-of-00030.safetensors... | 53ae9dafe8b3d163e05d75387575f8e9f43253d0 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"license:llama3",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|e... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "llama3", "license_name": "llama3", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Llama-3-70B-Instruct-abliterated Model Card
This is meta-llama/Llama-3-70B-Instruct with orthogonalized bfloat16 safetensor weights, generated with the methodology that was described in the preview paper/blog post: '[Refusal in LLMs is mediated by a single direction](https://www.alignmentforum.org/posts/jGuXSZgv6qfd... | null | [
"llama3",
"llama3",
"LICENSE"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64d063c77a7305c58943e530 | 6949732424a8d297 | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 42 | pankajmathur/orca_mini_v3_7b | pankajmathur | null | 1,580 | 108,837 | False | 2023-08-07T03:23:51Z | 2025-01-29T03:22:42Z | transformers | 40 | 0 | [{"name": "orca_mini_v3_7b", "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": 56.91, "name": "norma... | text-generation | {"parameters": {"F16": 6738415616}, "total": 6738415616} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"orca_minis_small.jpeg",
"pytorch_model-00001-of-00002.bin",
"pytorch_model-00002-of-00002.bin",
"pytorch_model.bin.inde... | 0cbb2b50ef8b6c4d512055dfdbf550fe5ce043c0 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:psmathur/orca_mini_v1_dataset",
"dataset:ehartford/dolphin",
"arxiv:2306.02707",
"arxiv:2302.13971",
"license:other",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "</s>", "lstrip": false, "normalized": true, "rstrip":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["psmathur/orca_mini_v1_dataset", "ehartford/dolphin"], "language": ["en"], "library_name": "transformers", "license": "other", "pipeline_tag": "text-generation", "model-index": [{"name": "orca_mini_v3_7b", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI... | # orca_mini_v3_7b
A LLama2-7b model trained on Orca Style datasets.
<br>
<br>
🤔 How good is orca-mini-v3-7b? Do the evaluation results from HuggingFace Open LLM leaderboard translate to real-world use cases?
🔍 Now y... | null | [
"other"
] | [
"psmathur/orca_mini_v1_dataset",
"ehartford/dolphin"
] | [
"en"
] | 6,738,415,616 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63b2b57554211fcd0626167a | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | microsoft/git-base-vatex | microsoft | null | 119 | 101,353 | False | 2023-01-02T10:44:05Z | 2023-09-15T19:52:10Z | transformers | 4 | 0 | null | image-text-to-text | {"parameters": {"I64": 1221, "F32": 176623674}, "total": 176624895} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"preprocessor_config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 623363cef8744c57438ce8d62b30bef1fbbec111 | [
"transformers",
"pytorch",
"safetensors",
"git",
"image-text-to-text",
"vision",
"en",
"arxiv:2205.14100",
"license:mit",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GitForCausalLM"], "model_type": "git", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "microsoft/git-base-vatex", "pipeline_tag": null, "tags": ["vision"], "inference": false} | # GIT (GenerativeImage2Text), base-sized, fine-tuned on VATEX
GIT (short for GenerativeImage2Text) model, base-sized version, fine-tuned on VATEX. It was introduced in the paper [GIT: A Generative Image-to-text Transformer for Vision and Language](https://arxiv.org/abs/2205.14100) by Wang et al. and first released in ... | null | [
"mit"
] | null | [
"en"
] | 176,624,895 | null | null | [
"AutoModelForImageTextToText",
"GitForCausalLM",
"git"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
621ffdc136468d709f17ba9f | 382b5a4eb98f0296 | d965e4a9140ecf72 | 21,128 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 33 | hfl/chinese-electra-180g-large-discriminator | hfl | null | 2,662 | 103,773 | False | 2022-03-02T23:29:05Z | 2021-03-03T01:29:12Z | transformers | 6 | 0 | null | null | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | d017e219578df8e4885484edbc8969dbdea9cbe0 | [
"transformers",
"pytorch",
"tf",
"electra",
"zh",
"arxiv:2004.13922",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"model_type": "electra", "tokenizer_config": {}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # This model is trained on 180G data, we recommend using this one than the original version.
## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size and relatively competitive performance compared to BERT and its variants.
For further accel... | null | [
"apache-2.0"
] | null | [
"zh"
] | null | null | null | [
"AutoModel",
"electra"
] | [
null
] | null | null | null |
67449278db3726cf00882554 | a1524adaa43b439b | 3e62a24f3d0a884f | 32,003 | BPE | 58,980 | true | false | true | true | 6 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 228 | trl-internal-testing/tiny-Idefics2ForConditionalGeneration | trl-internal-testing | null | 9,873 | 125,128 | False | 2024-11-25T15:06:32Z | 2025-12-19T19:13:02Z | transformers | 0 | 0 | null | image-text-to-text | {"parameters": {"F32": 3659072}, "total": 3659072} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"chat_template.json",
"config.json",
"generation_config.json",
"model.safetensors",
"preprocessor_config.json",
"processor_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_con... | 9cacf64f03691daca2b445b6346d1f138d71d96b | [
"transformers",
"safetensors",
"idefics2",
"image-text-to-text",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["Idefics2ForConditionalGeneration"], "model_type": "idefics2", "processor_config": {"chat_template": "{% for message in messages %}{{message['role'].capitalize()}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}{% if line['type'... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["trl"]} | # Tiny Idefics2ForConditionalGeneration
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 3,659,072 | null | null | [
"AutoModelForImageTextToText",
"Idefics2ForConditionalGeneration",
"idefics2"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
6531b5e0e7897259333a1412 | 02217ffa5907f57a | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 130 | oobabooga/CodeBooga-34B-v0.1 | oobabooga | null | 8,758 | 142,456 | False | 2023-10-19T23:04:00Z | 2024-01-02T23:01:35Z | transformers | 147 | 0 | null | text-generation | {"parameters": {"F16": 33743970304}, "total": 33743970304} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"model-00001-of-00008.safetensors",
"model-00002-of-00008.safetensors",
"model-00003-of-00008.safetensors",
"model-00004-of-00008.safetensors",
"model-00005-of-00008.safetensors",
"model-00006-of-00008.s... | 8a4e1e16ac46333cbd0c17d733d3d70a956071a6 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "</s>", "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # CodeBooga-34B-v0.1
This is a merge between the following two models:
1) [Phind-CodeLlama-34B-v2](https://huggingface.co/Phind/Phind-CodeLlama-34B-v2)
2) [WizardCoder-Python-34B-V1.0](https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0)
It was created with the [BlockMerge Gradient script](https://github.com... | null | [
"llama2"
] | null | null | 33,743,970,304 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
68ac91970e1f746cac314aa4 | 6c53decdf26fa934 | 21ca95dec54278ad | 151,678 | BPE | 151,387 | true | true | true | true | 35 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 820 | OpenGVLab/InternVL3_5-8B | OpenGVLab | {
"models": [
{
"_id": "68ac918f77cad47e1bf98d31",
"id": "OpenGVLab/InternVL3_5-8B-MPO"
}
],
"relation": "finetune"
} | 50,708 | 436,752 | False | 2025-08-25T16:38:47Z | 2025-08-29T17:57:06Z | transformers | 94 | 0 | null | image-text-to-text | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"configuration_intern_vit.py",
"configuration_internvl_chat.py",
"conversation.py",
"generation_config.json",
"merges.txt",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model... | 9bb6a56ad9cc69db95e2d4eeb15a52bbcac4ef79 | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"internvl",
"custom_code",
"image-text-to-text",
"conversational",
"multilingual",
"dataset:OpenGVLab/MMPR-v1.2",
"dataset:OpenGVLab/MMPR-Tiny",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.1... | null | {"architectures": ["InternVLChatModel"], "auto_map": {"AutoConfig": "configuration_internvl_chat.InternVLChatConfig", "AutoModel": "modeling_internvl_chat.InternVLChatModel", "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel"}, "model_type": "internvl_chat", "tokenizer_config": {"bos_token": null, "eos_... | {
"auto_model": "AutoModel",
"custom_class": "modeling_internvl_chat.InternVLChatModel",
"pipeline_tag": "feature-extraction",
"processor": null
} | {"base_model": ["OpenGVLab/InternVL3_5-8B-MPO"], "datasets": ["OpenGVLab/MMPR-v1.2", "OpenGVLab/MMPR-Tiny"], "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "imag... | # InternVL3_5-8B
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggingface.co/pap... | null | [
"apache-2.0"
] | [
"OpenGVLab/MMPR-v1.2",
"OpenGVLab/MMPR-Tiny"
] | [
"multilingual"
] | null | null | null | [
"AutoModel",
"internvl_chat",
"InternVLChatModel",
"modeling_internvl_chat.InternVLChatModel"
] | [
"image-text-to-text",
"feature-extraction"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text",
"embeddings"
] |
63b5505a9d50c1463c52b5f9 | fb120b2369a2dd99 | 51b83cb95a3c2287 | 32,000 | BPE | 31,783 | false | true | true | true | 4 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 946 | Daoguang/PyCodeGPT | Daoguang | null | 34 | 99,902 | False | 2023-01-04T10:09:30Z | 2023-01-04T10:21:24Z | transformers | 9 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 4d92041ffa3566aaf75ca6d33f3dfbc86e0403ec | [
"transformers",
"pytorch",
"gpt_neo",
"text-generation",
"license:afl-3.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTNeoForCausalLM"], "model_type": "gpt_neo", "tokenizer_config": {"unk_token": "<|unkoftext|>", "bos_token": "<|beginoftext|>", "eos_token": "<|endoftext|>", "pad_token": "<|padoftext|>"}} | {
"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": "afl-3.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # PyCodeGPT
A pre-trained GPT model for Python code completion and generation
## What is it?
PyCodeGPT is efficient and effective GPT-Neo-based model for python code generation task, which is similar to [OpenAI Codex](https://openai.com/blog/openai-codex/), [Github Copliot](https://copilot.github.com/), [CodeParrot](... | null | [
"afl-3.0"
] | null | null | null | null | null | [
"gpt_neo",
"AutoModelForCausalLM",
"GPTNeoForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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