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6243438322549d0917c2694f | f0b30459222b62d4 | 70bd27c212bc339c | 50,265 | BPE | 50,000 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
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The model is a `roberta-base` fine-tuned on [fake-and-real-news-dataset](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset). It has a 100% accuracy on that dataset.
The model takes a news article and predicts if it is true or fake.
The format of the input should be:
```
<title> ... | null | [
"mit"
] | null | [
"en"
] | null | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | garage-bAInd/Platypus2-13B | garage-bAInd | null | 844 | 103,899 | False | 2023-08-05T00:12:12Z | 2024-01-03T21:27:12Z | transformers | 17 | 0 | null | text-generation | {"parameters": {"F32": 2560, "F16": 13015864320}, "total": 13015866880} | [
".gitattributes",
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"pytorch_model-00002-o... | dc1024c1b9df38f57f6436a02d31706cb0deaa01 | [
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"safetensors",
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"arxiv:2308.07317",
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"license:cc-by-nc-sa-4.0",
"text-generation-inference",
"endpoints_compatible",
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] | 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": ["garage-bAInd/Open-Platypus"], "eval_results": null, "language": ["en"], "library_name": null, "license": "cc-by-nc-sa-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Platypus2-13B
Platypus-13B is an instruction fine-tuned model based on the LLaMA2-13B transformer architecture.
### Model Details
* **Trained by**: Cole Hunter & Ariel Lee
* **Model type:** **Platypus2-13B** is an auto-regressive language model based on the LLaMA2 transformer ... | null | [
"cc-by-nc-sa-4.0"
] | [
"garage-bAInd/Open-Platypus"
] | [
"en"
] | 13,015,866,880 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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661a86ced9dc3639eb1b1fc9 | 0aea00f578e27edb | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 904 | meraGPT/mera-mix-4x7B | meraGPT | null | 8,406 | 140,496 | False | 2024-04-13T13:21:18Z | 2024-04-20T00:58:30Z | transformers | 19 | 0 | [{"name": "mera-mix-4x7B", "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": 72.95, "name": "normali... | text-generation | {"parameters": {"BF16": 24153690112}, "total": 24153690112} | [
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"model-00002-of... | 09d965c5ef9b66ce419986027e03a915cb869e43 | [
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"endpoints_compatible",
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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",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"license": "apache-2.0", "model-index": [{"name": "mera-mix-4x7B", "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": "ac... | # Model mera-mix-4x7B
This is a mixture of experts (MoE) model that is half as large (4 experts instead of 8) as the [Mixtral-8x7B](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
while been comparable to it across different benchmarks. You can use it as a drop in replacement for your Mixtral-8x7B and get... | null | [
"apache-2.0"
] | null | null | 24,153,690,112 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
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] | [
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] | [
"text"
] | [
"text"
] |
6456741ad10badc9555cd78d | 10868aaafd17c266 | 787458edeef9a04f | 50,282 | BPE | 50,009 | true | true | true | true | 30 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 947 | liuhaotian/LLaVA-Lightning-MPT-7B-preview | liuhaotian | null | 37 | 99,784 | False | 2023-05-06T15:36:58Z | 2023-11-05T02:04:28Z | transformers | 54 | 0 | null | text-generation | null | [
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] | c770dd9ea32bcfa716a720f1654115db3fff8cd3 | [
"transformers",
"pytorch",
"llava_mpt",
"text-generation",
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] | null | {"architectures": ["LlavaMPTForCausalLM"], "model_type": "llava_mpt", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
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**NOTE: Unlike other LLaVA models, this model can (should) be used directly without delta weights conversion!**
<br>
<br>
# LLaVA Model Card
## M... | null | [
"cc-by-nc-sa-4.0"
] | null | null | null | null | null | [
"LlavaMPTForCausalLM",
"AutoModelForCausalLM",
"llava_mpt"
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"text-generation"
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6675566b568251b0b79b7ce9 | 5e330c9120012510 | 1dbd56bba92f6891 | 128,258 | BPE | 280,147 | false | true | true | true | 258 | null | Sequence | ByteLevel | null | [
"Split",
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] | 948 | stephenlzc/dolphin-llama3-zh-cn-uncensored | stephenlzc | {
"models": [
{
"_id": "66244c6c251ee52d52247964",
"id": "dphn/dolphin-2.9-llama3-8b"
}
],
"relation": "quantized"
} | 3,859 | 119,479 | False | 2024-06-21T10:31:07Z | 2024-06-24T17:44:54Z | transformers | 20 | 0 | null | text-generation | {"parameters": {"BF16": 8030277632}, "total": 8030277632} | [
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"dolphin-llama3-zh-cn-uncensored-unsloth.Q... | 2bf897b920c6c1fbb971216e4fd14ab1398b52b1 | [
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"NSFW",
"conversational",
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"dataset:llm-wizard/alpaca-gpt4-data-zh",
"dataset:stephenlzc/stf-alpaca",
"base_model:dphn/dolphin... | {"total": 8030277632, "architecture": "llama", "context_length": 8192, "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|>' + '\n'}}{% endfor %}{% if add... | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "cognitivecomputations/dolphin-2.9-llama3-8b", "datasets": ["Minami-su/toxic-sft-zh", "llm-wizard/alpaca-gpt4-data-zh", "stephenlzc/stf-alpaca"], "eval_results": null, "language": ["zh", "en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_nam... | ## Model Details
### Model Description
It's my first finetune exmaple.
Using `cognitivecomputations/dolphin-2.9-llama3-8b` as base model, and finetune with `Minami-su/toxic-sft-zh` and `llm-wizard/alpaca-gpt4-data-zh` to let tha model support Chinese.
## Training Procedure
[![Open In Colab](https://colab.research.g... | null | [
"mit"
] | [
"Minami-su/toxic-sft-zh",
"llm-wizard/alpaca-gpt4-data-zh",
"stephenlzc/stf-alpaca"
] | [
"zh",
"en"
] | 8,030,277,632 | 8,030,277,632 | null | [
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] | [
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621ffdc136468d709f177c11 | 79641b267692b72f | f87d7bfce4fd9617 | 30,000 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
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"Lowercase",
"Precompiled"
] | [
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"Metaspace"
] | 586 | XSY/albert-base-v2-fakenews-discriminator | XSY | null | 3,108 | 113,340 | False | 2022-03-02T23:29:05Z | 2021-11-16T13:11:50Z | transformers | 3 | 0 | [{"name": "albert-base-v2-fakenews-discriminator", "results": []}] | text-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# albert-base-v2-fakenews-discriminator
The dataset: Fake and real news dataset https://www.kaggle.com/clmentbisaillon/fake-and-real... | null | [
"apache-2.0"
] | null | null | null | null | [
"accuracy"
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"models": [
{
"_id": "6759799ed862e62a825b5413",
"id": "answerdotai/ModernBERT-base"
}
],
"relation": "finetune"
} | 4,988 | 108,468 | False | 2025-01-14T16:59:51Z | 2026-03-17T13:01:50Z | transformers | 10 | 0 | null | text-classification | {"parameters": {"F32": 149626396}, "total": 149626396} | [
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} | {"base_model": ["answerdotai/ModernBERT-base"], "datasets": ["go_emotions"], "eval_results": null, "language": "en", "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": ["accuracy", "f1", "precision", "recall", "matthews_correlation"], "model_name": null, "pipeline_t... | null | null | [
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65224528ef81ce01a46d1715 | 7935b8f626500ef9 | 830fa437e6f588f3 | 50,000 | BPE | 49,721 | true | true | true | true | 23 | NFKC | Sequence | ByteLevel | [
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"ByteLevel"
] | 499 | Norm/nougat-latex-base | Norm | null | 3,044 | 114,041 | False | 2023-10-08T05:59:04Z | 2024-02-26T17:07:04Z | transformers | 82 | 0 | null | image-to-text | {"parameters": {"I64": 48020, "F32": 348687992}, "total": 348736012} | [
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"image-text-to-text",
"image-to-text",
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] | null | {"architectures": ["VisionEncoderDecoderModel"], "model_type": "vision-encoder-decoder", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForImageTextToText",
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"pipeline_tag": "image-text-to-text",
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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": "image-to-text", "tags": null, "inference": {"parameters": {"max_length": 800}}} | # Nougat-LaTeX-based
- **Model type:** [Donut](https://huggingface.co/docs/transformers/model_doc/donut)
- **Finetuned from:** [facebook/nougat-base](https://huggingface.co/facebook/nougat-base)
- **Repository:** [source code](https://github.com/NormXU/nougat-latex-ocr)
Nougat-LaTeX-based is fine-tuned from [facebo... | null | [
"apache-2.0"
] | null | [
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685993401dc14f4f9f2d37bd | 46323c0f61df476d | 1fe366e13272caa0 | 262,145 | BPE | 514,906 | true | true | true | true | 6,415 | Replace | Split | Sequence | [
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} | 1,371 | 210,012 | False | 2025-06-23T17:47:44Z | 2025-06-23T17:52:00Z | transformers | 0 | 0 | null | image-text-to-text | {"parameters": {"BF16": 27432406640}, "total": 27432406640} | [
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"arxi... | null | {"architectures": ["Gemma3ForConditionalGeneration"], "model_type": "gemma3", "processor_config": {"chat_template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n {%- if messages[0]['content'] is string -%}\n {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n {%- else -%}\n ... | {
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<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/gemma-3-67d12b7e8816ec6efa7e4e5b">our collection</a> for all versions of Gemma 3 including GGUF, 4-bit & 16-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em><a href="https://docs.... | null | [
"gemma"
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"Strip",
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] | [
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] | [
"Metaspace"
] | 204 | sophiebottani/deberta_squadnewsqa | sophiebottani | null | 2 | 99,038 | False | 2023-05-17T20:09:42Z | 2023-05-18T07:07:16Z | transformers | 1 | 0 | [{"name": "deberta_squadnewsqa", "results": []}] | question-answering | null | [
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should probably proofread and complete it, then remove this comment. -->
# deberta_squadnewsqa
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3... | null | [
"mit"
] | [
"squad_v2",
"newsqa"
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6633a006de240abed19846e6 | d0a7f857964a0bb2 | aff5a8e9396e0d96 | 92,544 | BPE | 165,112 | true | false | true | true | 9 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 831 | chujiezheng/internlm2-chat-20b-ExPO | chujiezheng | null | 15,589 | 174,256 | False | 2024-05-02T14:15:34Z | 2024-05-27T18:16:15Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 19861149696}, "total": 19861149696} | [
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "zh"], "library_name": null, "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | # internlm2-chat-20b-ExPO
The extrapolated (ExPO) model based on [`internlm2-chat-20b`](https://huggingface.co/internlm/internlm2-chat-20b) and [`internlm/internlm2-chat-20b-sft`](https://huggingface.co/internlm/internlm2-chat-20b-sft), as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/ab... | null | [
"other"
] | null | [
"en",
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] | 19,861,149,696 | null | null | [
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"multimodal"
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"text"
] | [
"text",
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] |
62c490c3143622c92792badc | d4e318c40b3aa7f3 | 3e8e5f0f5d743dac | 50,000 | BPE | 49,797 | true | true | true | true | 1 | Sequence | Sequence | ByteLevel | [
"Lowercase",
"NFKC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 949 | ClassCat/gpt2-base-french | ClassCat | null | 233 | 99,378 | False | 2022-07-05T19:28:03Z | 2022-07-21T09:04:41Z | transformers | 6 | 0 | null | text-generation | null | [
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### Prerequisites
transformers==4.19.2
### Model architecture
This model uses GPT2 base setttings except vocabulary size.
### Tokenizer
Using BPE tokenizer with vocabulary size 50,000.
### Training Data
* [wiki40b/fr](https://www.tensorflow.org/datasets/catalog/wiki40b#wiki4... | null | [
"cc-by-sa-4.0"
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"wikipedia",
"cc100"
] | [
"fr"
] | null | null | null | [
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6504993e0761d34d28abc0e1 | e68b0b111c49dac2 | dd84a2b1ff97657d | 250,002 | Unigram | null | true | true | true | true | 5 | Precompiled | Sequence | Metaspace | [
"Precompiled"
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"WhitespaceSplit",
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"Metaspace"
] | 28 | jeffwan/mmarco-mMiniLMv2-L12-H384-v1 | jeffwan | null | 3,695 | 104,263 | False | 2023-09-15T17:49:50Z | 2023-09-15T18:17:35Z | transformers | 8 | 0 | null | text-classification | null | [
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"... | null | {"architectures": ["XLMRobertaForSequenceClassification"], "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": f... | {
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This model was trained on the [MMARCO](https://hf.co/unicamp-dl/mmarco) dataset. It is a machine translated version of MS MARCO using Google Translate. It was translated to 14 languages. In our experiments, we observed that it performs also well for other languages.
As a base... | null | [
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6852cbc9068d0068b5dba19c | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
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<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated... | null | null | null | null | 19,509,248 | null | null | [
"AutoModelForCausalLM",
"Qwen3ForCausalLM",
"qwen3"
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"text-generation"
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64954b2694d4926d8ed67023 | 3a732ab237c338af | c21f0239d1cf0f86 | 65,024 | BPE | 64,784 | false | true | false | true | 12 | null | Sequence | ByteLevel | null | [
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"Split"
] | [
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] | null | {"architectures": ["RWForCausalLM"], "auto_map": {"AutoConfig": "configuration_RW.RWConfig", "AutoModel": "modelling_RW.RWModel", "AutoModelForCausalLM": "modelling_RW.RWForCausalLM", "AutoModelForQuestionAnswering": "modelling_RW.RWForQuestionAnswering", "AutoModelForSequenceClassification": "modelling_RW.RWForSequenc... | {
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} | {"base_model": null, "datasets": ["OpenAssistant/oasst1"], "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": ["gpt", "llm", "large language model", "h2o-llmstud... | # Model Card
## Summary
This model was trained using [H2O LLM Studio](https://github.com/h2oai/h2o-llmstudio).
- Base model: [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
- Dataset preparation: [OpenAssistant/oasst1](https://github.com/h2oai/h2o-llmstudio/blob/1935d84d9caafed3ee686ad2733eb02d2abfce57/a... | null | [
"apache-2.0"
] | [
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] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"RWForCausalLM",
"RefinedWeb",
"modelling_RW.RWForCausalLM"
] | [
"text-generation"
] | [
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] | [
"text"
] | [
"text"
] |
66339e721806627c0046a5c0 | d0a7f857964a0bb2 | aff5a8e9396e0d96 | 92,544 | BPE | 165,112 | true | false | true | true | 9 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 831 | chujiezheng/internlm2-chat-7b-ExPO | chujiezheng | null | 15,582 | 174,161 | False | 2024-05-02T14:08:50Z | 2024-05-27T18:15:47Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"BF16": 7737708544}, "total": 7737708544} | [
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"conversational",
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"zh",
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] | null | {"architectures": ["InternLM2ForCausalLM"], "auto_map": {"AutoConfig": "configuration_internlm2.InternLM2Config", "AutoModel": "internlm/internlm2-chat-7b--modeling_internlm2.InternLM2ForCausalLM", "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM"}, "model_type": "internlm2", "tokenizer_config": {"bos_t... | {
"auto_model": "AutoModel",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "zh"], "library_name": null, "license": "other", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null} | # internlm2-chat-7b-ExPO
The extrapolated (ExPO) model based on [`internlm2-chat-7b`](https://huggingface.co/internlm/internlm2-chat-7b) and [`internlm/internlm2-chat-7b-sft`](https://huggingface.co/internlm/internlm2-chat-7b-sft), as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/abs/240... | null | [
"other"
] | null | [
"en",
"zh"
] | 7,737,708,544 | null | null | [
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"AutoModel",
"internlm2",
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] | [
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] | [
"text"
] | [
"text",
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] |
6872cd6de50ee1d7fbf0b099 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | onnx-internal-testing/tiny-random-ArceeForCausalLM | onnx-internal-testing | null | 4,027 | 126,429 | False | 2025-07-12T21:02:37Z | 2025-07-22T23:35:49Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"F32": 4129088}, "total": 4129088} | [
".gitattributes",
"README.md",
"chat_template.jinja",
"config.json",
"generation_config.json",
"model.safetensors",
"onnx/model.onnx",
"onnx/model.onnx_data",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
"tokenizer_config.json"
] | c79ee81209248b85203a9f7bdac7af834b0d7049 | [
"transformers",
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"safetensors",
"arcee",
"text-generation",
"conversational",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ArceeForCausalLM"], "model_type": "arcee", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": false}, "chat_template_jinja": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_m... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": []} | null | null | null | null | null | 4,129,088 | null | null | [
"ArceeForCausalLM",
"AutoModelForCausalLM",
"arcee"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6589a978a3bfb30fdbd2b2b3 | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | elyza/ELYZA-japanese-Llama-2-13b-instruct | elyza | null | 858 | 103,452 | False | 2023-12-25T16:10:32Z | 2023-12-27T01:41:15Z | transformers | 43 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"key_visual.png",
"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",
... | ed15089024f3ecad9a8c4ce1db302cc01aa9f4ee | [
"transformers",
"pytorch",
"llama",
"text-generation",
"ja",
"en",
"arxiv:2307.09288",
"license:llama2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<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": ["ja", "en"], "library_name": null, "license": "llama2", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | ## ELYZA-japanese-Llama-2-13b
### Model Description
**ELYZA-japanese-Llama-2-13b** は、 Llama 2をベースとして日本語能力を拡張するために追加事前学習を行ったモデルです。
詳細は [Blog記事](https://note.com/elyza/n/n5d42686b60b7) を参照してください。
### Usage
```python
import torch
from transformers import AutoModelForCa... | null | [
"llama2"
] | null | [
"ja",
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
655d7b796a37ab8e1c5dc6db | e23b6bdbe047bb7e | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | LoneStriker/Yarn-Llama-2-70b-32k-2.4bpw-h6-exl2 | LoneStriker | null | 1 | 22 | False | 2023-11-22T03:54:33Z | 2023-11-22T04:07:11Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"configuration_llama.py",
"generation_config.json",
"huggingface-metadata.txt",
"modeling_llama_yarn.py",
"output-00001-of-00003.safetensors",
"output-00002-of-00003.safetensors",
"output-00003-of-00003.safetensors",
"pytorch_m... | edce41b7e33e107af1562091a14ea907b6f6b662 | [
"transformers",
"pytorch",
"llama",
"text-generation",
"custom_code",
"en",
"dataset:emozilla/yarn-train-tokenized-8k-llama",
"arxiv:2309.00071",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "auto_map": {"AutoConfig": "configuration_llama.LlamaConfig", "AutoModelForCausalLM": "modeling_llama_yarn.LlamaForCausalLM"}, "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt"... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["emozilla/yarn-train-tokenized-8k-llama"], "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: Yarn-Llama-2-70b-32k
[Preprint (arXiv)](https://arxiv.org/abs/2309.00071)
[GitHub](https://github.com/jquesnelle/yarn)
The authors would like to thank [LAION AI](https://laion.ai/) for their suppor... | null | [
"apache-2.0"
] | [
"emozilla/yarn-train-tokenized-8k-llama"
] | [
"en"
] | null | null | [
"perplexity"
] | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65e6b17209de4d8e68afe845 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | abacusai/Liberated-Qwen1.5-14B | abacusai | null | 261 | 99,311 | False | 2024-03-05T05:45:22Z | 2024-03-05T05:53:24Z | transformers | 20 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"pytorch_model-00001-of-00006.bin",
"pytorch_model-00002-of-00006.bin",
"pytorch_model-00003-of-00006.bin",
"pytorch_model-00004-of-00006.bin",
"pytorch_model-00005-of-00006.bin",
"pytorc... | cc0fa5102bfee821bb5e49f082731ccb9d1fedf1 | [
"transformers",
"pytorch",
"qwen2",
"text-generation",
"conversational",
"en",
"dataset:teknium/OpenHermes-2.5",
"dataset:m-a-p/Code-Feedback",
"dataset:m-a-p/CodeFeedback-Filtered-Instruction",
"dataset:abacusai/SystemChat",
"license:other",
"text-generation-inference",
"endpoints_compatibl... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "tokenizer_config": {"bos_token": null, "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["teknium/OpenHermes-2.5", "m-a-p/Code-Feedback", "m-a-p/CodeFeedback-Filtered-Instruction", "abacusai/SystemChat"], "eval_results": null, "language": ["en"], "library_name": null, "license": "other", "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5... | <img href="https://abacus.ai" src="https://cdn-uploads.huggingface.co/production/uploads/64c14f6b02e1f8f67c73bd05/pf4d6FA7DriRtVq5HCkxd.png" width="600" />
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/xCWGByXr8YNwGxKVh_x9H.png" width="600" />
# Liberated-Qwen1.5-14B
Brought... | null | [
"other",
"tongyi-qianwen",
"https://huggingface.co/Qwen/Qwen1.5-72B/blob/main/LICENSE"
] | [
"teknium/OpenHermes-2.5",
"m-a-p/Code-Feedback",
"m-a-p/CodeFeedback-Filtered-Instruction",
"abacusai/SystemChat"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
654b1aa5e4ce07c7d7a0b34d | 34df1b8cec23ffbb | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 640 | DeepMount00/Mistral-Ita-7b | DeepMount00 | null | 1,285 | 104,428 | False | 2023-11-08T05:20:37Z | 2024-04-23T06:27:57Z | transformers | 42 | 0 | null | text-generation | {"parameters": {"BF16": 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.model",
"tokenizer_config.... | ae899f0d93762a20761a52476805957943bca1aa | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"text-generation-inference",
"text generation",
"it",
"dataset:DeepMount00/llm_ita_ultra",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "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": null, "datasets": ["DeepMount00/llm_ita_ultra"], "eval_results": null, "language": ["it"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text-generation-inference", "text generation"]} | # Mistral-7B-v0.1 for Italian Language Text Generation
## Model Architecture
- **Base Model:** [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
- **Specialization:** Italian Language
## Evaluation
For a detailed comparison of model performance, check out the [Leaderboard for Italian Language Model... | null | [
"apache-2.0"
] | [
"DeepMount00/llm_ita_ultra"
] | [
"it"
] | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65f5adb9ddf0619cb0fd54b8 | 3df3ae63280e4ab9 | 5cc89648c8003a49 | 256,000 | BPE | 580,604 | true | false | true | true | 6 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 950 | yam-peleg/Hebrew-Gemma-11B-V2 | yam-peleg | null | 5,106 | 121,621 | False | 2024-03-16T14:33:29Z | 2024-03-16T16:03:33Z | transformers | 12 | 0 | null | text-generation | {"parameters": {"BF16": 10475492352}, "total": 10475492352} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
"model-00003-of-00005.safetensors",
"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
"model.safetensors.index.json",
"special_tok... | bff43da660089d467a2b29a8cc8ead986b3277ca | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"conversational",
"en",
"he",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "tokenizer_config": {"bos_token": "<bos>", "chat_template": "{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ r... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "he"], "library_name": "transformers", "license": "other", "license_name": "gemma-terms-of-use", "license_link": "https://ai.google.dev/gemma/terms", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Hebrew-Gemma-11B-V2
An updated version of [Hebrew-Gemma-11B](https://huggingface.co/yam-peleg/Hebrew-Gemma-11B) that was trained longer and had some bugs fixes.
### Base Models:
- **07.03.2024:** [Hebrew-Gemma-11B](https://huggingface.co/yam-peleg/Hebrew-Gemma-11B)
- **16.03.2024:** [Hebrew-Gemma-11B-V2](https://hu... | null | [
"other",
"gemma-terms-of-use",
"https://ai.google.dev/gemma/terms"
] | null | [
"en",
"he"
] | 10,475,492,352 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
668cd8d85a19e1af67217362 | 803e3c8528c55bf1 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 352 | BAAI/Infinity-Instruct-3M-0625-Llama3-8B | BAAI | null | 7,895 | 136,910 | False | 2024-07-09T06:29:44Z | 2024-07-09T15:00:57Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
".gitattributes",
"README.md",
"config.json",
"fig/Bk3NbjnJko51MTx1ZCScT2sqnGg.png",
"fig/result.png",
"fig/trainingflow.png",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004.safetensors",... | 7be7c0ff1e35c3bb781c47222da99a1724f5f1da | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"en",
"dataset:BAAI/Infinity-Instruct",
"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": ["BAAI/Infinity-Instruct"], "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} | # Infinity Instruct
<p align="center">
<img src="fig/Bk3NbjnJko51MTx1ZCScT2sqnGg.png" width="300">
</p>
<p align="center">
<em>Beijing Academy of Artificial Intelligence (BAAI)</em><br/>
<em>[Paper][Code][🤗] (would be released soon)</em>
</p>
Infinity-Instruct-3M-0625-Llama3-8B is an opensource supervised instructio... | null | [
"apache-2.0"
] | [
"BAAI/Infinity-Instruct"
] | [
"en"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67d1ee871d28e9ef2ca7f89a | 03b2b331a48c71c3 | b14664993aa88526 | 100,278 | BPE | 100,000 | false | true | false | true | 22 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 199 | allenai/OLMo-2-0325-32B-Instruct | allenai | {
"models": [
{
"_id": "67d1ef5d0a6a6dd4a0d83e8f",
"id": "allenai/OLMo-2-0325-32B-DPO"
}
],
"relation": "finetune"
} | 13,462 | 130,232 | False | 2025-03-12T20:28:55Z | 2025-03-14T22:45:15Z | transformers | 148 | 0 | null | text-generation | {"parameters": {"BF16": 32234279936}, "total": 32234279936} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
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"model-00004-of-00014.safetensors",
"model-00005-of-00014.safetensors",
"model-00006-of-00014.safetens... | b96024342a77a69aa0dda815c3454a671f477463 | [
"transformers",
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"olmo2",
"text-generation",
"conversational",
"en",
"dataset:allenai/RLVR-GSM-MATH-IF-Mixed-Constraints",
"arxiv:2501.00656",
"arxiv:2411.15124",
"base_model:allenai/OLMo-2-0325-32B-DPO",
"base_model:finetune:allenai/OLMo-2-0325-32B-DPO",
"license:apache-2.0",
... | null | {"architectures": ["Olmo2ForCausalLM"], "model_type": "olmo2", "tokenizer_config": {"bos_token": "<|endoftext|>", "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{ '<|system|>\n' + message['content'] + '\n' }}{% elif message['role'] == 'user' %}{{ '<|user|>\n' + message['content'] + ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["allenai/OLMo-2-0325-32B-DPO"], "datasets": ["allenai/RLVR-GSM-MATH-IF-Mixed-Constraints"], "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... | <img alt="OLMo Logo" src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/olmo2/olmo.png" width="242px">
OLMo 2 32B Instruct March 2025 is post-trained variant of the [OLMo-2 32B March 2025](https://huggingface.co/allenai/OLMo-2-0325-32B/) model, which has undergone supervised finetuning on an OLMo-sp... | null | [
"apache-2.0"
] | [
"allenai/RLVR-GSM-MATH-IF-Mixed-Constraints"
] | [
"en"
] | 32,234,279,936 | null | null | [
"AutoModelForCausalLM",
"olmo2",
"Olmo2ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6811210db946c0939d9ce46f | 03b2b331a48c71c3 | b14664993aa88526 | 100,278 | BPE | 100,000 | false | true | false | true | 22 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 199 | allenai/OLMo-2-0425-1B-Instruct | allenai | {
"models": [
{
"_id": "6811431ad8654528b07a97b0",
"id": "allenai/OLMo-2-0425-1B-RLVR1"
}
],
"relation": "finetune"
} | 40,846 | 447,426 | False | 2025-04-29T18:57:17Z | 2025-04-30T22:32:46Z | transformers | 56 | 0 | null | text-generation | {"parameters": {"BF16": 1484916736}, "total": 1484916736} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 48d788eca847d4d7548f375ad03d3c9312f6139e | [
"transformers",
"safetensors",
"olmo2",
"text-generation",
"conversational",
"en",
"dataset:allenai/RLVR-MATH",
"arxiv:2501.00656",
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"base_model:finetune:allenai/OLMo-2-0425-1B-RLVR1",
"license:apache-2.0",
"endpoints_compatible",... | null | {"architectures": ["Olmo2ForCausalLM"], "model_type": "olmo2", "tokenizer_config": {"bos_token": "<|endoftext|>", "chat_template": "{{ bos_token }}{% for message in messages %}{% if message['role'] == 'system' %}{{ '<|system|>\n' + message['content'] + '\n' }}{% elif message['role'] == 'user' %}{{ '<|user|>\n' + messag... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["allenai/OLMo-2-0425-1B-RLVR1"], "datasets": ["allenai/RLVR-MATH"], "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} | null | null | [
"apache-2.0"
] | [
"allenai/RLVR-MATH"
] | [
"en"
] | 1,484,916,736 | null | null | [
"AutoModelForCausalLM",
"olmo2",
"Olmo2ForCausalLM"
] | [
"text-generation"
] | [
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"text"
] | [
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661d3188c1ba45d3a1024610 | c201230c641b14d0 | 5cc89648c8003a49 | 256,000 | BPE | 580,604 | true | false | true | true | 4 | Replace | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 161 | MoxoffSrL/Volare | MoxoffSrL | null | 2,414 | 106,104 | False | 2024-04-15T13:54:16Z | 2024-04-18T07:24:46Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"F16": 8537680896}, "total": 8537680896} | [
".gitattributes",
"README.md",
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"... | 41c187a3af2c932a41fa5b6ef1f9ff3abd56c9e7 | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"sft",
"it",
"chatml",
"en",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GemmaForCausalLM"], "model_type": "gemma", "tokenizer_config": {"bos_token": "<bos>", "eos_token": "<eos>", "pad_token": "<pad>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["it", "en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["sft", "it", "gemma", "chatml"]} | # Model Information
Volare is an updated version of [Gemma7B](https://huggingface.co/google/gemma-7b), specifically fine-tuned with SFT and LoRA adjustments.
- It's trained on publicly available datasets, like [SQUAD-it](https://huggingface.co/datasets/squad_it), and datasets we've created in-house.
- it's designed t... | null | [
"mit"
] | null | [
"it",
"en"
] | 8,537,680,896 | null | null | [
"AutoModelForCausalLM",
"gemma",
"GemmaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
666f72d9bfdba06d38f57e74 | 390af744e5565f11 | 101408923f784238 | 64,000 | WordPiece | null | true | true | true | true | 8 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 924 | Omartificial-Intelligence-Space/Arabert-all-nli-triplet-Matryoshka | Omartificial-Intelligence-Space | {
"models": [
{
"_id": "621ffdc136468d709f1794dc",
"id": "aubmindlab/bert-base-arabertv02"
}
],
"relation": "finetune"
} | 319 | 101,383 | False | 2024-06-16T23:18:49Z | 2025-01-23T10:26:16Z | sentence-transformers | 11 | 0 | [{"name": "Omartificial-Intelligence-Space/Arabert-all-nli-triplet-Matryoshka", "results": [{"dataset": {"config": "ar", "name": "MTEB MIRACLRetrieval (ar)", "revision": "main", "split": "dev", "type": "miracl/mmteb-miracl"}, "metrics": [{"type": "ndcg_at_1", "value": 9.289, "verified": false}, {"type": "ndcg_at_3", "v... | sentence-similarity | {"parameters": {"F32": 135193344}, "total": 135193344} | [
".gitattributes",
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"README.md",
"config.json",
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"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | e5f7a347099c35f0dea6f25692bd86f05e3fcdeb | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"mteb",
"transformers",
"sentence-similarity",
"generated_from_trainer",
"dataset_size:557850",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"ar",
"dataset:Omartificial-Intelligence-Space/Arabic-NLi-Triplet"... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": "aubmindlab/bert-base-arabertv02", "datasets": ["Omartificial-Intelligence-Space/Arabic-NLi-Triplet"], "language": ["ar"], "library_name": "sentence-transformers", "license": "apache-2.0", "metrics": ["pearson_cosine", "spearman_cosine", "pearson_manhattan", "spearman_manhattan", "pearson_euclidean", "sp... | # Arabert All NLI Triplet Matryoshka Model
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the Omartificial-Intelligence-Space/arabic-n_li-triplet dataset. It maps sentences & paragraphs to a 768-... | null | [
"apache-2.0"
] | [
"Omartificial-Intelligence-Space/Arabic-NLi-Triplet"
] | [
"ar"
] | 135,193,344 | null | [
"pearson_cosine",
"spearman_cosine",
"pearson_manhattan",
"spearman_manhattan",
"pearson_euclidean",
"spearman_euclidean",
"pearson_dot",
"spearman_dot",
"pearson_max",
"spearman_max"
] | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
63f780501cb66f416c6e190c | ab139ece4cbf7569 | 37c80f16d904da76 | 32,005 | Unigram | null | true | true | true | true | 8 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 951 | almanach/camembert-bio-base | almanach | null | 5,129 | 113,021 | False | 2023-02-23T15:03:44Z | 2025-09-25T16:48:13Z | transformers | 20 | 0 | null | fill-mask | {"parameters": {"I64": 514, "F32": 110655493}, "total": 110656007} | [
".gitattributes",
".gitignore",
"README.md",
"camembert-bio-logo.png",
"config.json",
"model.safetensors",
"neuron/config.json",
"neuron/model.neuron",
"neuron/sentencepiece.bpe.model",
"neuron/special_tokens_map.json",
"neuron/tokenizer.json",
"neuron/tokenizer_config.json",
"pytorch_model.... | 5fbdc71cc8b8b59f9e40229ff1d5baa1808ffde6 | [
"transformers",
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"fill-mask",
"biomedical",
"clinical",
"life sciences",
"neuron",
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"dataset:rntc/biomed-fr",
"doi:10.57967/hf/0586",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["CamembertForMaskedLM"], "model_type": "camembert", "tokenizer_config": {"bos_token": "<s>", "cls_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "sep_token": "</s>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["rntc/biomed-fr"], "eval_results": null, "language": ["fr"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "fill-mask", "tags": ["biomedical", "clinical", "life sciences", "neuron"], "w... | null | null | [
"mit"
] | [
"rntc/biomed-fr"
] | [
"fr"
] | 110,656,007 | null | null | [
"CamembertForMaskedLM",
"AutoModelForMaskedLM",
"camembert"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
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67b3bd303770f4f5d68bd2eb | 897e472a76b74290 | ca60ee72fe371096 | 49,155 | BPE | 48,891 | false | true | true | true | 22 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 367 | ibm-granite/granite-vision-3.2-2b | ibm-granite | {
"models": [
{
"_id": "6753571bc050f63baedf520f",
"id": "ibm-granite/granite-3.1-2b-instruct"
}
],
"relation": "finetune"
} | 2,161 | 125,809 | False | 2025-02-17T22:50:24Z | 2025-06-12T02:15:13Z | transformers | 123 | 0 | null | image-text-to-text | {"parameters": {"BF16": 2975396928}, "total": 2975396928} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.json",
"config.json",
"example.png",
"generation_config.json",
"merges.txt",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"preprocessor_config.json",
"processor_confi... | 2818ae5b93cb750b099df1b65f7864e4a0401271 | [
"transformers",
"safetensors",
"llava_next",
"image-text-to-text",
"conversational",
"en",
"arxiv:2502.09927",
"base_model:ibm-granite/granite-3.1-2b-instruct",
"base_model:finetune:ibm-granite/granite-3.1-2b-instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",... | null | {"architectures": ["LlavaNextForConditionalGeneration"], "model_type": "llava_next", "processor_config": {"chat_template": "{%- if tools %}\n {{- '<|start_of_role|>available_tools<|end_of_role|>\n' }}\n {%- for tool in tools %}\n {{- tool | tojson(indent=4) }}\n {%- if not loop.last %}\n {{- '\n\n' }... | {
"auto_model": "AutoModelForImageTextToText",
"custom_class": null,
"pipeline_tag": "image-text-to-text",
"processor": "AutoProcessor"
} | {"base_model": ["ibm-granite/granite-3.1-2b-instruct"], "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "new_version": "ibm-granite/gr... | # granite-vision-3.2-2b
**Model Summary:**
granite-vision-3.2-2b is a compact and efficient vision-language model, specifically designed for visual document understanding, enabling automated content extraction from tables, charts, infographics, plots, diagrams, and more. The model was trained on a meticulously curated... | null | [
"apache-2.0"
] | null | [
"en"
] | 2,975,396,928 | null | null | [
"AutoModelForImageTextToText",
"LlavaNextForConditionalGeneration",
"llava_next"
] | [
"image-text-to-text"
] | [
"multimodal"
] | [
"text",
"image"
] | [
"text"
] |
6695ee3076cb4dac841bf273 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | lmms-lab/LLaVA-NeXT-Video-32B-Qwen | lmms-lab | null | 184 | 101,185 | False | 2024-07-16T03:51:12Z | 2024-10-04T08:56:41Z | transformers | 17 | 0 | null | video-text-to-text | {"parameters": {"BF16": 32942093856}, "total": 32942093856} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model-00001-of-00014.safetensors",
"model-00002-of-00014.safetensors",
"model-00003-of-00014.safetensors",
"model-00004-of-00014.safetensors",
"model-00005-of-00014.safetensors",
"model-... | 95291f9ac7904761b346d95b9b7c7090cc3bb029 | [
"transformers",
"safetensors",
"llava",
"text-generation",
"video-text-to-text",
"arxiv:2410.02713",
"license:apache-2.0",
"region:us"
] | null | {"architectures": ["LlavaQwenForCausalLM"], "model_type": "llava", "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<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoProcessor"
} | {"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": "video-text-to-text", "tags": null, "inference": false} | <br>
## LLaVA-NeXT-Video is upgraded 🚀
In our [LLaVA-Video blog](https://llava-vl.github.io/blog/2024-04-30-llava-next-video/) released this April, we shared two key observations:
- 🎬 AnyRes provides a shared and flexible representation between images and videos, and thus accommodates capability transfer between t... | null | [
"apache-2.0"
] | null | null | 32,942,093,856 | null | null | [
"AutoModelForCausalLM",
"LlavaQwenForCausalLM",
"llava"
] | [
"video-text-to-text",
"text-generation"
] | [
"text",
"vision"
] | [
"text",
"image"
] | [
"text"
] |
65ee931c7443c0926729b6b5 | 02217ffa5907f57a | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 130 | sophosympatheia/Midnight-Miqu-70B-v1.5 | sophosympatheia | {
"models": [
{
"_id": "65e3b8a6607c2f5380421ffb",
"id": "migtissera/Tess-70B-v1.6"
},
{
"_id": "65e012a1ebc538ecfac4cd1c",
"id": "sophosympatheia/Midnight-Miqu-70B-v1.0"
}
],
"relation": "merge"
} | 11,205 | 142,689 | False | 2024-03-11T05:14:04Z | 2024-12-10T16:50:16Z | transformers | 252 | 4 | [{"name": "Midnight-Miqu-70B-v1.5", "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": 61.18, "name": "strict ... | text-generation | {"parameters": {"F16": 68976648192}, "total": 68976648192} | [
".gitattributes",
"LICENSE",
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"mergekit_config.yml",
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... | 74888979a3734f0d7466d77dbf32120f575000e3 | [
"transformers",
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"conversational",
"arxiv:2311.03099",
"base_model:migtissera/Tess-70B-v1.6",
"base_model:merge:migtissera/Tess-70B-v1.6",
"base_model:sophosympatheia/Midnight-Miqu-70B-v1.0",
"base_model:merge:sophosympatheia/Midni... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "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": ["sophosympatheia/Midnight-Miqu-70B-v1.0", "migtissera/Tess-70B-v1.6"], "library_name": "transformers", "license": "other", "tags": ["mergekit", "merge"], "model-index": [{"name": "Midnight-Miqu-70B-v1.5", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "I... | <div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/Tn9MBg6.png" alt="MidnightMiqu" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
### Overview
Looking for the 103B version? You can get it from [FluffyKaeloky/Midnight-Miqu-103B-v1.5](https://hug... | null | [
"other"
] | null | null | 68,976,648,192 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65fb8fb6ca9a46d48445dca2 | 2699d1261ea2d637 | cf7a052aa6fec7ad | 30,000 | BPE | 15,977 | true | true | true | true | 229 | Sequence | Metaspace | Metaspace | [
"NFKC",
"BertNormalizer"
] | [
"Metaspace"
] | [
"Metaspace"
] | 952 | EbanLee/kobart-summary-v3 | EbanLee | null | 67,348 | 175,030 | False | 2024-03-21T01:39:02Z | 2025-03-13T00:51:44Z | transformers | 21 | 0 | null | summarization | {"parameters": {"F32": 123889968}, "total": 123889968} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | cff33231c01ed86c7f08de5c05c597b7ef2f0bfc | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"summarization",
"ko",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BartForConditionalGeneration"], "model_type": "bart", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "mask_token": "<mask>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-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": ["rouge"], "model_name": null, "pipeline_tag": "summarization", "tags": ["bart"]} | # kobart-summary
- 이 모델은 [kobart모델](https://huggingface.co/hyunwoongko/kobart)을 [문서요약](https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=97), [도서자료요약](https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=data&dataSetSn=93), [요약문 및 레포트 생성](http... | null | null | null | [
"ko"
] | 123,889,968 | null | [
"rouge"
] | [
"bart",
"BartForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66f83ce856a2aa7fe934981d | 51d5ab0d0cb758dc | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 208 | sdadas/stella-pl-retrieval | sdadas | null | 80,724 | 216,227 | False | 2024-09-28T17:29:12Z | 2026-02-12T12:52:19Z | sentence-transformers | 13 | 0 | null | sentence-similarity | {"parameters": {"F32": 1543268864}, "total": 1543268864} | [
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... | 5f7ff9b7e9d413457ee88f9d9affa982f54b2fc0 | [
"sentence-transformers",
"safetensors",
"qwen2",
"text-generation",
"feature-extraction",
"sentence-similarity",
"transformers",
"custom_code",
"pl",
"license:gemma",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen2ForCausalLM"], "auto_map": {"AutoConfig": "configuration_qwen.Qwen2Config", "AutoModel": "modeling_qwen.Qwen2Model", "AutoModelForCausalLM": "modeling_qwen.Qwen2ForCausalLM", "AutoModelForSequenceClassification": "modeling_qwen.Qwen2ForSequenceClassification"}, "model_type": "qwen2", "tokenizer... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "pl", "library_name": null, "license": "gemma", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", ... | <h1 align="center">Stella-PL-retrieval</h1>
This is a text encoder based on [stella_en_1.5B_v5](https://huggingface.co/dunzhang/stella_en_1.5B_v5) and further fine-tuned for Polish information retrieval tasks.
- In the first step, we adapted the model for Polish with [multilingual knowledge distillation method](https... | null | [
"gemma"
] | null | [
"pl"
] | 1,543,268,864 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"sentence-similarity",
"feature-extraction",
"text-generation"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"text",
"embeddings"
] |
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"NFC"
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"ByteLevel"
] | 953 | naver-hyperclovax/HyperCLOVAX-SEED-Think-14B | naver-hyperclovax | null | 36,263 | 214,139 | False | 2025-07-21T06:49:46Z | 2025-08-27T16:03:19Z | transformers | 112 | 0 | null | text-generation | null | [
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"auto_model": "AutoModelForCausalLM",
"custom_class": "modeling_hyperclovax.HyperCLOVAXForCausalLM",
"pipeline_tag": "text-generation",
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "other", "license_name": "hyperclovax-seed", "license_link": "LICENSE", "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | 
## Overview
HyperCLOVA X SEED 14B Think is a next-generation language model that moves beyond the conventional approach of simply increasing model size to improve performance. It combines [HyperCLOVA... | null | [
"other",
"hyperclovax-seed",
"LICENSE"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"HyperCLOVAXForCausalLM",
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] | [
"text"
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"text"
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"text"
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"Prepend",
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"Replace",
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] | 42 | McGill-NLP/LLM2Vec-Sheared-LLaMA-mntp | McGill-NLP | null | 247 | 325,106 | False | 2024-04-04T13:53:05Z | 2024-05-21T22:00:57Z | transformers | 6 | 0 | null | sentence-similarity | null | [
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"Sentence S... | null | {"architectures": ["LlamaEncoderModel"], "auto_map": {"AutoModel": "McGill-NLP/LLM2Vec-Sheared-LLaMA-mntp--modeling_llama_encoder.LlamaEncoderModel"}, "model_type": "llama", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": "</s>", "unk_token": "<unk>", "use_default_system_prompt": false}} | {
"auto_model": "AutoModel",
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"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["text-embedding", "embeddings", "information-retrieval", "be... | # LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
> LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine... | null | [
"mit"
] | null | [
"en"
] | null | null | null | [
"llama",
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"McGill-NLP/LLM2Vec-Sheared-LLaMA-mntp--modeling_llama_encoder.LlamaEncoderModel",
"LlamaEncoderModel"
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"text-classification"
] | [
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"multimodal"
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"text"
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621ffdc136468d709f180b46 | 9a415b19aec14031 | ad4b234fa1a3ca7b | 31,102 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 857 | svalabs/gbert-large-zeroshot-nli | svalabs | null | 13,502 | 157,057 | False | 2022-03-02T23:29:05Z | 2025-06-04T14:42:57Z | transformers | 11 | 0 | null | zero-shot-classification | null | [
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] | 5530b8082e02fe7a0b397ec10d8f51cf481efa01 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"nli",
"de",
"zero-shot-classification",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
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"pipeline_tag": "text-classification",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": "de", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "zero-shot-classification", "tags": ["text-classification", "pytorch", "nli", "de"], "widget": [{"text": ... | # SVALabs - Gbert Large Zeroshot Nli
In this repository, we present our German zeroshot classification model.
This model was trained on the basis of the German BERT large model from [deepset.ai](https://huggingface.co/deepset/gbert-large) and finetuned for natural language inference based on 847.862 machine-transl... | null | null | null | [
"de"
] | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
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"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
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"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 299 | EleutherAI/polyglot-ko-3.8b | EleutherAI | null | 175 | 99,902 | False | 2022-09-09T14:15:36Z | 2023-06-07T05:03:23Z | transformers | 24 | 0 | null | text-generation | {"parameters": {"F32": 1024, "F16": 3809974272, "BOOL": 134217728}, "total": 3944193024} | [
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"text-generation-inference",
"endpoints_compatible",
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"region:us"
] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"eos_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ko"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["pytorch", "causal-lm"]} | # Polyglot-Ko-3.8B
## Model Description
Polyglot-Ko is a series of large-scale Korean autoregressive language models made by the EleutherAI polyglot team.
| Hyperparameter | Value |
|... | null | [
"apache-2.0"
] | null | [
"ko"
] | 3,944,193,024 | null | null | [
"gpt_neox",
"AutoModelForCausalLM",
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"text"
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621ffdc136468d709f17acfa | dd4f9ee07a05851c | 5d0543b90d3ada56 | 32,004 | Unigram | null | true | true | true | true | 7 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 20 | AgentPublic/dpr-question_encoder-fr_qa-camembert | AgentPublic | null | 267 | 98,872 | False | 2022-03-02T23:29:05Z | 2021-06-16T10:10:09Z | transformers | 8 | 0 | null | feature-extraction | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"tokenizer.json",
"vocab.txt"
] | 20f81e3505a3184dbf3729701d7c6152125287ef | [
"transformers",
"pytorch",
"camembert",
"feature-extraction",
"fr",
"dataset:piaf",
"dataset:FQuAD",
"dataset:SQuAD-FR",
"arxiv:2004.04906",
"arxiv:1911.03894",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DPRQuestionEncoder"], "model_type": "camembert"} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["piaf", "FQuAD", "SQuAD-FR"], "eval_results": null, "language": "fr", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # dpr-question_encoder-fr_qa-camembert
## Description
French [DPR model](https://arxiv.org/abs/2004.04906) using [CamemBERT](https://arxiv.org/abs/1911.03894) as base and then fine-tuned on a combo of three French Q&A
## Data
### French Q&A
We use a combination of three French Q&A datasets:
1. [PIAFv1.1](https://... | null | null | [
"piaf",
"FQuAD",
"SQuAD-FR"
] | [
"fr"
] | null | null | null | [
"AutoModel",
"camembert",
"DPRQuestionEncoder"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
6655f8c27473f3c2577fcf29 | ccf483eb28c1c710 | d05332da13658bea | 120,138 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 71 | aidarmusin/address-ner-ru | aidarmusin | null | 200 | 98,833 | False | 2024-05-28T15:31:14Z | 2024-07-10T12:59:08Z | transformers | 11 | 0 | null | token-classification | {"parameters": {"F32": 425878547}, "total": 425878547} | [
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"ru",
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] | 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",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["ru"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["ner"], "widget": [{"text": "628672, \u0410\u0432\u0442\u043e\u043d\u043e\u043c\... | # address-ner-ru
Address NER model to find address parts from string
[https://huggingface.co/aidarmusin/address-ner-ru](https://huggingface.co/aidarmusin/address-ner-ru)
# Dataset
5K raw addresses dataset
90% for training and 10% for evaluation
# Evaluation
| Metric | Value |
| --- | --- |
| eval_overall_precisi... | null | [
"apache-2.0"
] | null | [
"ru"
] | 425,878,547 | null | null | [
"AutoModelForTokenClassification",
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"bert"
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"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
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621ffdc136468d709f17adb3 | 4211ba98bb2477fe | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
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"BertPreTokenizer"
] | [
"WordPiece"
] | 870 | fabriceyhc/bert-base-uncased-yahoo_answers_topics | fabriceyhc | null | 20 | 97,840 | False | 2022-03-02T23:29:05Z | 2021-09-21T00:54:22Z | transformers | 3 | 0 | [{"name": "bert-base-uncased-yahoo_answers_topics", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "yahoo_answers_topics", "type": "yahoo_answers_topics", "args": "yahoo_answers_topics"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value": 0.7499166666... | text-classification | null | [
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} | {"datasets": ["yahoo_answers_topics"], "license": "apache-2.0", "metrics": ["accuracy"], "tags": ["generated_from_trainer", "sibyl"], "model-index": [{"name": "bert-base-uncased-yahoo_answers_topics", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "yahoo_answers... | <!-- 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-base-uncased-yahoo_answers_topics
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base... | null | [
"apache-2.0"
] | [
"yahoo_answers_topics"
] | null | null | null | [
"accuracy"
] | [
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] | [
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] | [
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] | [
"text"
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"logits"
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] | 94 | ByteDance-Seed/academic-ds-9B | ByteDance-Seed | null | 21,980 | 186,012 | False | 2025-04-09T13:02:51Z | 2025-04-09T14:53:16Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"BF16": 9366498240}, "total": 9366498240} | [
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"en"
] | 9,366,498,240 | null | null | [
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"ByteFallback",
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] | 800 | RedHatAI/TinyLlama-1.1B-Chat-v1.0-marlin | RedHatAI | {
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{
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"id": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
}
],
"relation": "quantized"
} | 4,460 | 104,809 | False | 2024-03-05T19:17:33Z | 2024-03-06T01:00:38Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"I32": 121110528, "F16": 139127808}, "total": 260238336} | [
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"special_tokens_map.json",
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] | 29715d88e87589af7a9c6992ad5a94a2b8f1792a | [
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"conversational",
"arxiv:2210.17323",
"base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"base_model:quantized:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"text-generation-inference",
"endpoints_compatible",
"4-... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "quantization_config": {"bits": 4, "quant_method": "gptq"}, "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['r... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "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": ["nm-vllm", "marlin", "int4"], "inference": true, "model_ty... | null | null | null | null | null | 260,238,336 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
665619a02fd2e8a25b161b82 | 6e6a83dc4b556c95 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 111 | failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5 | failspy | null | 8,446 | 138,818 | False | 2024-05-28T17:51:28Z | 2024-05-30T14:27:00Z | transformers | 53 | 0 | null | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"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",
"model-0... | fc951b03d92972ab52ad9392e620eba6173526b9 | [
"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": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Llama-3-70B-Instruct-abliterated-v3.5 Model Card
[My original Jupyter "cookbook" to replicate the methodology can be found here](https://huggingface.co/failspy/llama-3-70B-Instruct-abliterated/blob/main/ortho_cookbook.ipynb)
[My personal library o' code used](https://github.com/FailSpy/abliterator) (WIP, looking to... | null | [
"llama3"
] | null | null | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6374f7beb93cbdf65675a215 | a2eba66f56003a7a | 830fa437e6f588f3 | 50,000 | BPE | 49,721 | true | true | false | true | 23 | NFKC | Sequence | ByteLevel | [
"NFKC"
] | [
"Split",
"Digits",
"Split",
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 439 | facebook/galactica-30b | facebook | null | 908 | 102,047 | False | 2022-11-16T14:46:22Z | 2023-01-24T17:20:45Z | transformers | 40 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"pytorch_model-00001-of-00007.bin",
"pytorch_model-00002-of-00007.bin",
"pytorch_model-00003-of-00007.bin",
"pytorch_model-00004-of-00007.bin",
"pytorch_model-00005-of-00007.bin",
"pytorch_model-00006-of-00007.bin",
"pytorch... | 80bd55898b06c7c363c467dec877b8b32702a2c4 | [
"transformers",
"pytorch",
"opt",
"text-generation",
"galactica",
"arxiv:1810.03993",
"license:cc-by-nc-4.0",
"text-generation-inference",
"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 30 B (large)
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 model c... | null | [
"cc-by-nc-4.0"
] | null | null | null | null | null | [
"OPTForCausalLM",
"AutoModelForCausalLM",
"opt"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6509230aed23af2c5d0ea348 | 88acfecb6bf60bca | 66151ebedb5c6113 | 37,120 | BPE | 60,819 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 954 | OpenBuddy/openbuddy-openllama-7b-v12-bf16 | OpenBuddy | null | 2,303 | 110,773 | False | 2023-09-19T04:26:50Z | 2023-09-20T06:40:33Z | transformers | 3 | 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.model",
"tokenizer_config.json"
] | bb94ff691996484b1a9d899a6c0956ef6750d86a | [
"transformers",
"pytorch",
"llama",
"text-generation",
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru",
"license:apache-2.0",
"text-generation-inference",
"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": ["zh", "en", "fr", "de", "ja", "ko", "it", "ru"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": null, "inference... | # 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)
## Disclaimer
All OpenBu... | null | [
"apache-2.0"
] | null | [
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
63294d56cf29bb7c68d8a3fd | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | impira/layoutlm-document-classifier | impira | null | 92 | 97,549 | False | 2022-09-20T05:19:18Z | 2022-11-03T20:03:22Z | transformers | 14 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 3f2dc7ed21a1290059c9c5e80e2bdf96b632902b | [
"transformers",
"pytorch",
"layoutlm",
"text-classification",
"document-classification",
"pdf",
"invoices",
"en",
"arxiv:1912.13318",
"arxiv:1910.09700",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LayoutLMForSequenceClassification"], "model_type": "layoutlm", "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": null, "eval_results": null, "language": "en", "library_name": null, "license": "cc-by-nc-sa-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["layoutlm", "document-classification", "pdf", "invoices"]} | # Model Card for LayoutLM for Document Classification
# Model Details
## Model Description
This is a fine-tuned version of the multi-modal LayoutLM model for the task of classification on documents.
- **Developed by:** Impira team
- **Shared by [Optional]:** Hugging Face
- **Model type:** Text Classification... | null | [
"cc-by-nc-sa-4.0"
] | null | [
"en"
] | null | null | null | [
"layoutlm",
"AutoModelForSequenceClassification",
"LayoutLMForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6661e5298829a4a8e117bad3 | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | unsloth/Qwen2-0.5B-Instruct-bnb-4bit | unsloth | null | 1,374 | 111,782 | False | 2024-06-06T16:34:49Z | 2024-09-03T03:45:34Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"F32": 67536, "BF16": 136206208, "U8": 369065940}, "total": 505339684} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 9af10e32642b18ed62373ea49fe628970279ee54 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"conversational",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": null, "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_star... | {
"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", "qwen2"]} | # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
We have a Google Colab Tesla T4 notebook for Qwen2 7b here: https://colab.research.google.com/drive/1mvwsIQWDs2EdZxZQF9pRGnnOvE86MVvR?usp=sharing
And a Colab notebook for [Qwen2 0.5b](https://colab.research.google.com/drive/1-7tjDdMAyeCueyL... | null | [
"apache-2.0"
] | null | [
"en"
] | 505,339,684 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66c87db20d38f15892b5aade | f5e7f943c396c76b | ddde944c7b357600 | 32,011 | BPE | 61,249 | true | false | true | true | 14 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 52 | anakin87/Phi-3.5-mini-ITA | anakin87 | {
"models": [
{
"_id": "66bfbb1a43a701a837a745ac",
"id": "microsoft/Phi-3.5-mini-instruct"
}
],
"relation": "finetune"
} | 5,164 | 111,499 | False | 2024-08-23T12:16:50Z | 2026-03-24T23:08:03Z | transformers | 13 | 0 | null | text-generation | {"parameters": {"BF16": 3821079552}, "total": 3821079552} | [
".gitattributes",
"README.md",
"added_tokens.json",
"assets/phi_35_mini_ita.png",
"config.json",
"generation_config.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors",
"model.safetensors.index.json",
"notebooks/training.ipynb",
"special_tokens_map.json",
"tokenizer.j... | 3058a5d0ce080781062c67ec94fde5a28edbad6b | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"trl",
"spectrum",
"conversational",
"custom_code",
"it",
"en",
"dataset:mlabonne/FineTome-100k",
"dataset:efederici/capybara-claude-15k-ita",
"arxiv:2406.06623",
"base_model:microsoft/Phi-3.5-mini-instruct",
"base_model:finetune:... | null | {"architectures": ["Phi3ForCausalLM"], "auto_map": {"AutoConfig": "microsoft/Phi-3.5-mini-instruct--configuration_phi3.Phi3Config", "AutoModelForCausalLM": "microsoft/Phi-3.5-mini-instruct--modeling_phi3.Phi3ForCausalLM"}, "model_type": "phi3", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message i... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "microsoft/Phi-3.5-mini-instruct", "datasets": ["mlabonne/FineTome-100k", "efederici/capybara-claude-15k-ita"], "eval_results": null, "language": ["it", "en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag"... | <img src="./assets/phi_35_mini_ita.png" width="450"></img>
# Phi-3.5-mini-ITA
Fine-tuned version of [Microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) optimized for better performance in Italian.
🔹 Small yet powerful model with 3.82 billion parameters
🔹 Supports 128k context l... | null | [
"mit"
] | [
"mlabonne/FineTome-100k",
"efederici/capybara-claude-15k-ita"
] | [
"it",
"en"
] | 3,821,079,552 | null | null | [
"AutoModelForCausalLM",
"phi3",
"Phi3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65c86f6897971388a5b29e5a | 0aea00f578e27edb | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 904 | jsfs11/MixtureofMerges-MoE-4x7b-v4 | jsfs11 | {
"models": [
{
"_id": "65c804a7426afc72472d5404",
"id": "Kukedlc/NeuTrixOmniBe-7B-model-remix"
},
{
"_id": "65b0756f6eaa79e358f5fcec",
"id": "PetroGPT/WestSeverus-7B-DPO"
},
{
"_id": "65b6d3f1625ac670a7d85887",
"id": "flemmingmiguel/MBX-7B-v3"
},
{
... | 7,960 | 135,314 | False | 2024-02-11T06:55:36Z | 2024-03-03T00:04:37Z | transformers | 4 | 0 | [{"name": "MixtureofMerges-MoE-4x7b-v4", "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": 72.53, "n... | text-generation | {"parameters": {"BF16": 24153690112}, "total": 24153690112} | [
".gitattributes",
"README.md",
"config.json",
"mergekit_moe_config.yml",
"model-00001-of-00005.safetensors",
"model-00002-of-00005.safetensors",
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"model-00004-of-00005.safetensors",
"model-00005-of-00005.safetensors",
"model.safetensors.index.json",
"special_to... | 2b98406f20a874184dbffb5ed24e1f4b5063ec4b | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"frankenmoe",
"merge",
"mergekit",
"lazymergekit",
"flemmingmiguel/MBX-7B-v3",
"Kukedlc/NeuTrixOmniBe-7B-model-remix",
"PetroGPT/WestSeverus-7B-DPO",
"vanillaOVO/supermario_v4",
"base_model:Kukedlc/NeuTrixOmniBe-7B-model-r... | 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": ["flemmingmiguel/MBX-7B-v3", "Kukedlc/NeuTrixOmniBe-7B-model-remix", "PetroGPT/WestSeverus-7B-DPO", "vanillaOVO/supermario_v4"], "license": "apache-2.0", "tags": ["moe", "frankenmoe", "merge", "mergekit", "lazymergekit", "flemmingmiguel/MBX-7B-v3", "Kukedlc/NeuTrixOmniBe-7B-model-remix", "PetroGPT/WestSe... | # MixtureofMerges-MoE-4x7b-v4
MixtureofMerges-MoE-4x7b-v4 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [flemmingmiguel/MBX-7B-v3](https://huggingface.co/flemmingmiguel/MBX-7B-v3)
* [Kukedlc/Neu... | null | [
"apache-2.0"
] | null | null | 24,153,690,112 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
668cd8977f96b8303737d98f | 302e00ef85417c9b | 3f3879d485dc5e16 | 63,992 | BPE | 110,029 | true | false | false | true | 231 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"Strip",
"ByteFallback",
"Fuse"
] | 527 | BAAI/Infinity-Instruct-3M-0625-Yi-1.5-9B | BAAI | null | 7,864 | 135,180 | False | 2024-07-09T06:28:39Z | 2024-07-22T07:51:47Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"BF16": 8829407232}, "total": 8829407232} | [
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"README.md",
"config.json",
"fig/Bk3NbjnJko51MTx1ZCScT2sqnGg.png",
"fig/result.png",
"fig/temp",
"fig/trainingflow.png",
"generation_config.json",
"model-00001-of-00004.safetensors",
"model-00002-of-00004.safetensors",
"model-00003-of-00004.safetensors",
"model-00004-of-00004... | a42c86c61b98ca4fdf238d688fe6ea11cf414d29 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"en",
"dataset:BAAI/Infinity-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|startoftext|>", "chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ system_message }}{% endif %}{% for message in mes... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["BAAI/Infinity-Instruct"], "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} | # Infinity Instruct
<p align="center">
<img src="fig/Bk3NbjnJko51MTx1ZCScT2sqnGg.png" width="300">
</p>
<p align="center">
<em>Beijing Academy of Artificial Intelligence (BAAI)</em><br/>
<em>[Paper][Code][🤗] (would be released soon)</em>
</p>
Infinity-Instruct-3M-0625-Yi-1.5-9B is an opensource supervised instructio... | null | [
"apache-2.0"
] | [
"BAAI/Infinity-Instruct"
] | [
"en"
] | 8,829,407,232 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f17b1a6 | 2dd48e4aa2022696 | 07b140dfd94cdbb2 | 50,257 | BPE | 49,995 | false | true | true | true | 6 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 955 | flax-community/papuGaPT2 | flax-community | null | 1,556 | 101,980 | False | 2022-03-02T23:29:05Z | 2021-07-21T15:46:46Z | transformers | 12 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"allegro_reviews/config.json",
"allegro_reviews/create_config_allegro.py",
"allegro_reviews/events.out.tfevents.1625481245.t1v-n-5d840006-w-0.20165.3.v2",
"allegro_reviews/events.out.tfevents.1625482183.t1v-n-5d840006-w-0.22476.3.v2",
"allegro_review... | 092abd8591c2fd021a1a32d9d51c49a3b6b3786a | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"text-generation",
"pl",
"endpoints_compatible",
"region:us"
] | null | null | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "pl", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text-generation"], "widget": [{"text": "Najsmaczniejszy polski owoc to"}]} | # papuGaPT2 - Polish GPT2 language model
[GPT2](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) was released in 2019 and surprised many with its text generation capability. However, up until very recently, we have not had a strong text generation model... | null | null | null | [
"pl"
] | null | null | null | [
"AutoModel"
] | [
null,
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66968312a6b069206ad465f1 | 60123cdc977c9538 | b0dd9ab9dbccb44d | 128,259 | BPE | 280,147 | false | true | true | true | 259 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 956 | AnatoliiPotapov/T-lite-instruct-0.1 | AnatoliiPotapov | null | 25 | 98,811 | False | 2024-07-16T14:26:26Z | 2024-09-25T10:44:32Z | transformers | 104 | 0 | null | text-generation | {"parameters": {"BF16": 8030285824}, "total": 8030285824} | [
".gitattributes",
"LICENSE",
"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",
"tokeniz... | d346cb648c2e302461edfe72528f1999d2ef88b5 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"ru",
"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": ["ru"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # T-lite-instruct-0.1
**🚨 T-lite is designed for further fine-tuning and is not intended as a ready-to-use conversational assistant. Users are advised to exercise caution and are responsible for any additional training and oversight required to ensure the model's responses meet acceptable ethical and safety standards... | null | null | null | [
"ru"
] | 8,030,285,824 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65fd90e82e0fbd5b874898d8 | 80b9827713daf135 | 313e1f7816f45106 | 151,851 | BPE | 151,387 | false | true | true | true | 208 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 833 | davidkim205/Rhea-72b-v0.5 | davidkim205 | null | 8,492 | 138,198 | False | 2024-03-22T14:08:40Z | 2024-04-08T05:23:20Z | transformers | 135 | 0 | [{"name": "Rhea-72b-v0.5", "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": 79.78, "name": "normali... | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"merges.txt",
"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.safetens... | bc3806efb23d2713e6630a748d9747fd76b27169 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"en",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"language": ["en"], "library_name": "transformers", "license": "apache-2.0", "model-index": [{"name": "Rhea-72b-v0.5", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "ar... | # Rhea-72b-v0.5
The Rhea project is a project that conducts research on various learning methods to improve llm model performance. We fine-tuned the existing model using the [nox](https://github.c... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6590309643edad216925b1e5 | 0aea00f578e27edb | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 904 | shadowml/Mixolar-4x7b | shadowml | null | 8,465 | 138,169 | False | 2023-12-30T15:00:38Z | 2024-04-01T16:01:05Z | transformers | 3 | 0 | [{"name": "Mixolar-4x7b", "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": 71.08, "name": "normaliz... | text-generation | {"parameters": {"F16": 36099461120}, "total": 36099461120} | [
".gitattributes",
"README.md",
"config.json",
"model-00001-of-00008.safetensors",
"model-00002-of-00008.safetensors",
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"model-00005-of-00008.safetensors",
"model-00006-of-00008.safetensors",
"model-00007-of-00008.safetensors",
... | bb793526b063765e9861cad8834160fb0945e66d | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"merge",
"mergekit",
"conversational",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{% if message['content']%}{{'### System:\n' + message['content']+'\n\n'}}{% endif %}{% elif message['role'] == 'user' %}{{'### Us... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"license": "apache-2.0", "tags": ["moe", "merge", "mergekit"], "model-index": [{"name": "Mixolar-4x7b", "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_... | # Mixolar-4x7b
This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
* [kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct)
* [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co... | null | [
"apache-2.0"
] | null | null | 36,099,461,120 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6647950aa1b232fd739137c3 | 803e3c8528c55bf1 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 352 | abacusai/Smaug-Llama-3-70B-Instruct | abacusai | null | 8,500 | 138,428 | False | 2024-05-17T17:34:02Z | 2024-06-04T21:41:27Z | transformers | 144 | 0 | null | text-generation | {"parameters": {"BF16": 70553706496}, "total": 70553706496} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00030.safetensors",
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"model-00004-of-00030.safetensors",
"model-00005-of-00030.safetensors",
"model-00006-of-00030.safetensors",
"model-0... | 8f558d6211b9d8f1712b80df40c5b65bea0b56ea | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"dataset:aqua_rat",
"dataset:microsoft/orca-math-word-problems-200k",
"dataset:m-a-p/CodeFeedback-Filtered-Instruction",
"arxiv:2402.13228",
"license:llama3",
"text-generation-inference",
"endpoints_compatible",
"re... | 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": ["aqua_rat", "microsoft/orca-math-word-problems-200k", "m-a-p/CodeFeedback-Filtered-Instruction"], "eval_results": null, "language": null, "library_name": "transformers", "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag"... | # Smaug-Llama-3-70B-Instruct
### Built with Meta Llama 3
This model was built using a new Smaug recipe for improving performance on real world multi-turn conversations applied to
[meta-llama/Meta... | null | [
"llama3"
] | [
"aqua_rat",
"microsoft/orca-math-word-problems-200k",
"m-a-p/CodeFeedback-Filtered-Instruction"
] | null | 70,553,706,496 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67bfbcd73859b01651fa087c | ffd0fdaf30c1f997 | a1bafba7a189a03a | 200,030 | BPE | 199,742 | false | true | false | true | 14 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 957 | unsloth/Phi-4-mini-instruct | unsloth | {
"models": [
{
"_id": "67b52d4a824d77f2bba8b0af",
"id": "microsoft/Phi-4-mini-instruct"
}
],
"relation": "finetune"
} | 7,249 | 118,638 | False | 2025-02-27T01:16:07Z | 2025-07-31T10:51:49Z | transformers | 24 | 0 | null | text-generation | {"parameters": {"BF16": 3836021760}, "total": 3836021760} | [
".gitattributes",
"README.md",
"added_tokens.json",
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"modeling_phi3.py",
"special_tokens_map.json",
"tokenize... | 75becc471c56fc34761ec998615ca6f8535c5a61 | [
"transformers",
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"unsloth",
"nlp",
"code",
"microsoft",
"math",
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"conversational",
"custom_code",
"multilingual",
"base_model:microsoft/Phi-4-mini-instruct",
"base_model:finetune:microsoft/Phi-4-mini-instruct",
"license... | null | {"architectures": ["Phi3ForCausalLM"], "auto_map": {"AutoConfig": "configuration_phi3.Phi3Config", "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM", "AutoTokenizer": "Xenova/gpt-4o"}, "model_type": "phi3", "tokenizer_config": {"bos_token": "<|endoftext|>", "chat_template": "{% for message in messages %}{% if mes... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "microsoft/Phi-4-mini-instruct", "datasets": null, "eval_results": null, "language": ["multilingual"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": "https://huggingface.co/microsoft/Phi-4-mini-instruct/resolve/main/LICENSE", "metrics": null, "model_name": null, ... | null | null | [
"mit",
"https://huggingface.co/microsoft/Phi-4-mini-instruct/resolve/main/LICENSE"
] | null | [
"multilingual"
] | 3,836,021,760 | null | null | [
"AutoModelForCausalLM",
"phi3",
"Phi3ForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
651d0ece11c17f8dec00a389 | 02217ffa5907f57a | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 130 | hyunseoki/ko-ref-llama2-7b | hyunseoki | null | 783 | 101,051 | False | 2023-10-04T07:05:50Z | 2023-10-04T07:22:05Z | transformers | 3 | 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.model",
"tokenizer_config.json"
] | 1ee08c79ae7393473754b77e82b1472ef63d5dd2 | [
"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-ref-llama2-7b is an auto-regressive language model based on the LLaMA2 transformer architecture.
**Base Model**
Llama-2-7B
**Training Dat... | null | null | null | [
"ko"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65368158c33220a87282637a | 8a8c94e1a59f5186 | ef4806e2ade9022f | 32,100 | Unigram | null | true | true | true | true | 103 | Precompiled | Sequence | Metaspace | [
"Precompiled"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 11 | facebook/musicgen-stereo-medium | facebook | null | 730 | 100,572 | False | 2023-10-23T14:21:12Z | 2024-03-06T14:47:27Z | transformers | 34 | 0 | null | text-to-audio | {"parameters": {"F16": 2035674182}, "total": 2035674182} | [
".gitattributes",
"README.md",
"compression_state_dict.bin",
"config.json",
"generation_config.json",
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"model.safetensors.index.fp32.json",
"preprocessor_config.json",
"pytorch_model.bin",
"pytorch_model.bin.index.fp32.json",
"pytorch_model.bin.index.json",
"special_tokens_... | 2747e613fbaadc43b14257224326ef58c5c11b81 | [
"transformers",
"pytorch",
"safetensors",
"musicgen",
"text-to-audio",
"audiocraft",
"arxiv:2306.05284",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MusicgenForConditionalGeneration"], "model_type": "musicgen", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForTextToWaveform",
"custom_class": null,
"pipeline_tag": "text-to-audio",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "cc-by-nc-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-to-audio", "tags": ["musicgen", "audiocraft"], "inference": true, "widget": [{"... | # MusicGen - Stereo - Medium - 1.5B
We further release a set of stereophonic capable models. Those were fine tuned for 200k updates starting
from the mono models. The training data is otherwise identical and capabilities and limitations are shared with the base modes. The stereo models work by getting 2 streams of tok... | null | [
"cc-by-nc-4.0"
] | null | null | 2,035,674,182 | null | null | [
"musicgen",
"MusicgenForConditionalGeneration",
"AutoModelForTextToWaveform"
] | [
"text-to-audio"
] | [
"text"
] | [
"text"
] | [
"audio"
] |
660a52162c198b9518bdbc0c | 34093184d10f76a9 | 35b001f3a491f9f9 | 151,646 | BPE | 151,387 | true | true | true | true | 3 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 53 | Qwen/Qwen1.5-32B-Chat-GPTQ-Int4 | Qwen | null | 2,656 | 107,386 | False | 2024-04-01T06:20:06Z | 2024-04-30T07:24:15Z | transformers | 30 | 0 | null | text-generation | {"parameters": {"I32": 31205621760, "F16": 1562448896}, "total": 32768070656} | [
".gitattributes",
"LICENSE",
"README.md",
"config.json",
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"merges.txt",
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"qwen2",
"text-generation",
"chat",
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"en",
"arxiv:2309.16609",
"license:other",
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"deploy:azure",
"region:us"
] | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"bits": 4, "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": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "other", "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-32B-Chat-GPTQ-Int4/blob/main/LICENSE", "metrics": null, "model_name": null, "pipeline_tag": "text-generation",... | # Qwen1.5-32B-Chat-GPTQ-Int4
> [!Warning]
> <div align="center">
> <b>
> 🚨 Please do not deploy this model with vLLM temporarily. Instead we advise you to use the AWQ model.
> </b>
> </div>
## Introduction
Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large a... | null | [
"other",
"tongyi-qianwen",
"https://huggingface.co/Qwen/Qwen1.5-32B-Chat-GPTQ-Int4/blob/main/LICENSE"
] | null | [
"en"
] | 32,768,070,656 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
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"text-generation",
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"en",
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"arxiv:2405.00675",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
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] | 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",
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} | {"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)
# Mistral7B-PairRM-SPPO-Iter3
This model was developed using [Self-Play Preference Optimization](https://arxiv.org/abs/2405.00675) at iteration 3, based on the [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/... | null | [
"apache-2.0"
] | [
"openbmb/UltraFeedback"
] | [
"en"
] | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66f28288cde8095a38867ee4 | aa22a75c2b649cab | 3222bc29782d2790 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
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] | [
"ByteLevel"
] | 878 | tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1 | tokyotech-llm | null | 279 | 101,384 | False | 2024-09-24T09:12:40Z | 2025-04-02T09:14:39Z | transformers | 17 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
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... | f82e2c268c583ca82f372bbc6825d19122e10bca | [
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"dataset:tokyotech-llm/swallow-magpie-ultra-v0.1",
"dataset:tokyotech-llm/swallow-gemma-magp... | 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": ["lmsys/lmsys-chat-1m", "tokyotech-llm/lmsys-chat-1m-synth", "argilla/magpie-ultra-v0.1", "tokyotech-llm/swallow-magpie-ultra-v0.1", "tokyotech-llm/swallow-gemma-magpie-v0.1"], "eval_results": null, "language": ["en", "ja"], "library_name": "transformers", "license": ["llama3.1", "gemma... | # Llama 3.1 Swallow - Built with Llama
Llama 3.1 Swallow is a series of large language models (8B, 70B) that were built by continual pre-training on the [Meta Llama 3.1](https://huggingface.co/collections/meta-llama/llama-31-669fc079a0c406a149a5738f) models.
Llama 3.1 Swallow enhanced the Japanese language capabilitie... | null | [
"llama3.1",
"gemma"
] | [
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"tokyotech-llm/lmsys-chat-1m-synth",
"argilla/magpie-ultra-v0.1",
"tokyotech-llm/swallow-magpie-ultra-v0.1",
"tokyotech-llm/swallow-gemma-magpie-v0.1"
] | [
"en",
"ja"
] | 8,030,261,248 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6629fb96dd2e78c931821f6b | 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-full | lightblue | {
"models": [
{
"_id": "6627253888596f571aedfb4a",
"id": "lightblue/suzume-llama-3-8B-multilingual"
}
],
"relation": "finetune"
} | 7,845 | 134,459 | False | 2024-04-25T06:43:34Z | 2024-05-30T09:58:05Z | transformers | 2 | 0 | [{"name": "workspace/llm_training/axolotl/llama3-multilingual-orpo/output_mitsu_full_borda", "results": []}] | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
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"... | ac04e23fb8861c188f8ecddfecc4250b40aee04d | [
"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_full_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"
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"text-generation"
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"text"
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"text"
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68813cdca1846ad54e4d5e88 | 44603641e8a34147 | e6ffdc5dd5f1fd86 | 256,000 | BPE | 580,604 | true | true | true | true | 249 | Replace | Metaspace | Sequence | [
"Replace"
] | [
"Metaspace"
] | [
"Replace",
"ByteFallback",
"Fuse"
] | 958 | jhu-clsp/mmBERT-base | jhu-clsp | null | 314,290 | 1,463,622 | False | 2025-07-23T19:49:48Z | 2025-10-07T14:08:42Z | transformers | 198 | 3 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
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] | c5955035435e2bf121cde7f3c8863ef52ff35d82 | [
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"ada",
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"adh",
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"a... | null | {"architectures": ["ModernBertForMaskedLM"], "model_type": "modernbert", "tokenizer_config": {"bos_token": "<bos>", "cls_token": "<bos>", "eos_token": "<eos>", "sep_token": "<eos>", "pad_token": "<pad>", "mask_token": "<mask>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["jhu-clsp/mmbert-decay", "jhu-clsp/mmbert-midtraining", "jhu-clsp/mmbert-pretrain-p1-fineweb2-langs", "jhu-clsp/mmbert-pretrain-p2-fineweb2-remaining", "jhu-clsp/mmbert-pretrain-p3-others"], "eval_results": null, "language": ["aai", "aak", "aau", "aaz", "aba", "abi", "abk", "abn", "abq... | # mmBERT: A Modern Multilingual Encoder
[](https://opensource.org/licenses/MIT)
[](https://arxiv.org/abs/2509.06888)
[](https://... | null | [
"mit"
] | [
"jhu-clsp/mmbert-decay",
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"Prepend",
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"Replace",
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] | 309 | aboonaji/llama2finetune-v2 | aboonaji | null | 452 | 98,168 | False | 2023-08-08T16:08:47Z | 2023-08-08T16:14:00Z | transformers | 8 | 0 | null | text-generation | null | [
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"endpoints_compatible",
"region:us"
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65cfdb0550818a335a39c722 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 0 | Lihuchen/pearl_base | Lihuchen | null | 72 | 98,049 | False | 2024-02-16T22:00:37Z | 2024-03-06T16:14:00Z | sentence-transformers | 3 | 0 | null | feature-extraction | {"parameters": {"F32": 109482240}, "total": 109482240} | [
".gitattributes",
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"modules.json",
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] | 1a45ebad338b38e5947ea604bef84f69b030a480 | [
"sentence-transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"Phrase Representation",
"String Matching",
"Fuzzy Join",
"Entity Retrieval",
"transformers",
"en",
"arxiv:2401.10407",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:az... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": 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": ["Phrase Representation", "String Matching", "Fuzzy Join", "Entity Retrieval", "t... | ## PEARL-base
[Learning High-Quality and General-Purpose Phrase Representations](https://arxiv.org/pdf/2401.10407.pdf). <br>
[Lihu Chen](https://chenlihu.com), [Gaël Varoquaux](https://gael-varoquaux.info/), [Fabian M. Suchanek](https://suchanek.name/).
<br> Accepted by EACL Findings 2024
PEARL-base is a lightweight... | null | [
"apache-2.0"
] | null | [
"en"
] | 109,482,240 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
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"embeddings"
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663d1b13d67a4c20c6d55bb4 | 634a9186a6003172 | 5f9f736c7dc6fbfa | 28,996 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 8 | TenzinGayche/Bert-large-book-genre-classification | TenzinGayche | null | 7 | 96,403 | False | 2024-05-09T18:50:59Z | 2024-05-09T19:01:50Z | transformers | 1 | 0 | null | text-classification | {"parameters": {"F32": 333612064}, "total": 333612064} | [
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"arxiv:1910.09700",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
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] | 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"
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<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated... | null | null | null | null | 333,612,064 | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
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"text"
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"text"
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"logits"
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66367c65e48c957c34f27839 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
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"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | UCLA-AGI/Mistral7B-PairRM-SPPO-Iter2 | UCLA-AGI | null | 8,348 | 137,214 | False | 2024-05-04T18:20:21Z | 2024-05-06T20:39:14Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
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"arxiv:2405.00675",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
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"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)
# Mistral7B-PairRM-SPPO-Iter2
This model was developed using [Self-Play Preference Optimization](https://arxiv.org/abs/2405.00675) at iteration 2, based on the [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/... | null | [
"apache-2.0"
] | [
"openbmb/UltraFeedback"
] | [
"en"
] | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65be3e4a259bc6caeb230081 | 11cdf776a252dffe | 7c4c85b636f4813b | 64,000 | BPE | 110,029 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 903 | cloudyu/TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO_f16 | cloudyu | null | 8,509 | 137,675 | False | 2024-02-03T13:23:22Z | 2024-11-01T00:46:34Z | transformers | 15 | 0 | null | text-generation | {"parameters": {"BF16": 60813892608}, "total": 60813892608} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00025.safetensors",
"model-00002-of-00025.safetensors",
"model-00003-of-00025.safetensors",
"model-00004-of-00025.safetensors",
"model-00005-of-00025.safetensors",
"model-00006-of-00025.safetensors",
"model-0... | a542d3348dd0361c4a1e3371f337121e0398a220 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"yi",
"moe",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{%- for idx in range(0, messages|length) -%}\n{%- if messages[idx]['role'] == 'user' -%}\n{%- if idx > 1 -%}\n{{- bos_token + '[INST] ' + messages[idx]['content'] + ' [/INST]' -}}\n{%- else -%}\... | {
"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": ["yi", "moe"]} | this is a DPO fine-tuned MoE model for [TomGrc/FusionNet_34Bx2_MoE_v0.1](https://huggingface.co/TomGrc/FusionNet_34Bx2_MoE_v0.1)
```
DPO Trainer
TRL supports the DPO Trainer for training language models from preference data, as described in the paper Direct Preference Optimization: Your Language Model is Secretly ... | null | [
"apache-2.0"
] | null | null | 60,813,892,608 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
64c9c425cbcae9f106fd830f | 02217ffa5907f57a | 8bd7d71767538b82 | 32,000 | BPE | 61,249 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 130 | pankajmathur/Lima_Unchained_70b | pankajmathur | null | 1,022 | 100,961 | False | 2023-08-02T02:49:09Z | 2025-09-19T14:31:31Z | transformers | 5 | 0 | [{"name": "test_42_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": 68.26, "name": "normalize... | text-generation | {"parameters": {"F16": 68976648192}, "total": 68976648192} | [
".gitattributes",
"README.md",
"config.json",
"generation_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-0... | 8f25fde3de697109a110367a25c37db874cd0341 | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:psmathur/lima_unchained_v1",
"arxiv:2305.11206",
"license:llama2",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<s>", "lstrip": false, "normalized": 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"
} | {"datasets": ["psmathur/lima_unchained_v1"], "language": ["en"], "library_name": "transformers", "license": "llama2", "model-index": [{"name": "test_42_70b", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config":... | # Lima_Unchained_70b
A Llama2-70b model fine-tuned using QLora on all the linear layers with carefully selected ~900 conversations from the [Lima](https://arxiv.org/pdf/2305.11206.pdf)
<br>
**P.S. If you're interested to collaborate, please connect with me at www.linkedin.com/in/pankajam.**
## Evaluation
We eval... | null | [
"llama2"
] | [
"psmathur/lima_unchained_v1"
] | [
"en"
] | 68,976,648,192 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65af032e48481b399a1c82b9 | 1c2b94bc65ea16ba | 7c4c85b636f4813b | 64,000 | BPE | 110,029 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse"
] | 919 | cloudyu/Yi-34Bx2-MoE-60B-DPO | cloudyu | null | 8,497 | 137,580 | False | 2024-01-23T00:07:10Z | 2024-08-06T07:56:54Z | transformers | 3 | 0 | [{"name": "Yi-34Bx2-MoE-60B-DPO", "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": 53.19, "name": "strict ac... | text-generation | {"parameters": {"BF16": 60813892608}, "total": 60813892608} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model-00001-of-00025.safetensors",
"model-00002-of-00025.safetensors",
"model-00003-of-00025.safetensors",
"model-00004-of-00025.safetensors",
"model-00005-of-00025.safetensors",
"model-00006-of-00025.safetensors",
"model-0... | 9687a84e69a2e1e61c4f526004c5a0fa77a3793f | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"yi",
"moe",
"DPO",
"conversational",
"license:apache-2.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "{%- for idx in range(0, messages|length) -%}\n{%- if messages[idx]['role'] == 'user' -%}\n{%- if idx > 1 -%}\n{{- bos_token + '[INST] ' + messages[idx]['content'] + ' [/INST]' -}}\n{%- else -%}\... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"license": "apache-2.0", "tags": ["yi", "moe", "DPO"], "model-index": [{"name": "Yi-34Bx2-MoE-60B-DPO", "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_stri... | * [This is DPO improved version of cloudyu/Yi-34Bx2-MoE-60B](https://huggingface.co/cloudyu/Yi-34Bx2-MoE-60B)
* [DPO Trainer](https://huggingface.co/docs/trl/main/en/dpo_trainer)
* metrics not test!
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
... | null | [
"apache-2.0"
] | null | null | 60,813,892,608 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66f16a55fcc1c455f8924842 | 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-3-13b-instruct | llm-jp | null | 314 | 100,028 | False | 2024-09-23T13:17:09Z | 2024-09-26T18:21:20Z | transformers | 31 | 0 | null | text-generation | {"parameters": {"BF16": 13707924480}, "total": 13707924480} | [
".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... | 000859051942cdbe6b812874984be05a153941f6 | [
"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-3-13b-instruct
This repository provides 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/).
The development was partially supported by [GENIAC](https://www.meti.go.jp... | null | [
"apache-2.0"
] | null | [
"en",
"ja"
] | 13,707,924,480 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
67b1a1f6178f02820b993ea9 | bfe694f64f4a18f5 | daab2a732bab72e2 | 128,001 | Unigram | null | true | true | true | true | 5 | Sequence | Sequence | Metaspace | [
"Strip",
"Precompiled",
"Replace"
] | [
"Metaspace"
] | [
"Metaspace"
] | 22 | desklib/ai-text-detector-v1.01 | desklib | {
"models": [
{
"_id": "621ffdc136468d709f17dee5",
"id": "microsoft/deberta-v3-large"
}
],
"relation": "finetune"
} | 89,243 | 402,295 | False | 2025-02-16T08:29:42Z | 2025-02-17T06:11:06Z | transformers | 40 | 0 | null | text-classification | {"parameters": {"F32": 434013185}, "total": 434013185} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"model.safetensors",
"special_tokens_map.json",
"spm.model",
"tokenizer.json",
"tokenizer_config.json"
] | 5fdea974cd4287c61674951ec78803aa274e2fb7 | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"en",
"dataset:liamdugan/raid",
"base_model:microsoft/deberta-v3-large",
"base_model:finetune:microsoft/deberta-v3-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DesklibAIDetectionModel"], "model_type": "deberta-v2", "tokenizer_config": {"bos_token": "[CLS]", "cls_token": "[CLS]", "eos_token": "[SEP]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": "AutoTokenizer"
} | {"base_model": ["microsoft/deberta-v3-large"], "datasets": ["liamdugan/raid"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": null} | # desklib/ai-text-detector-v1.01
## Overview
This AI-generated text detection model, developed by Desklib, is designed to classify English text as either human-written or AI-generated. It currently leads the [RAID Benchmark for AI Detection](https://raid-bench.xyz/leaderboard?domain=all&decoding=all&repetition=all&at... | null | [
"mit"
] | [
"liamdugan/raid"
] | [
"en"
] | 434,013,185 | null | null | [
"DesklibAIDetectionModel",
"AutoModel",
"deberta-v2"
] | [
null,
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
663e491f1e459d29d36f717c | 1399e7b7c54fd00b | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 959 | Eurdem/Defne_llama3_2x8B | Eurdem | null | 16 | 99,495 | False | 2024-05-10T16:19:43Z | 2024-05-16T09:01:01Z | transformers | 6 | 0 | null | text-generation | {"parameters": {"BF16": 13667667968}, "total": 13667667968} | [
".gitattributes",
"README.md",
"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"
] | c7f39aa11fbe198a802eda76e1b1797338c54491 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"merge",
"llama-3",
"conversational",
"en",
"tr",
"license:llama3",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MixtralForCausalLM"], "model_type": "mixtral", "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 + ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "tr"], "library_name": "transformers", "license": "llama3", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["moe", "merge", "llama-3"]} | ## 💻 For English
Defne_llama3_2x8B is a Mixure of Experts (MoE) (two llama3 models).
(Change the system prompt for Turkish as shown below)
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "Eurdem/Defne_llama3_2x8B"
... | null | [
"llama3"
] | null | [
"en",
"tr"
] | 13,667,667,968 | null | null | [
"mixtral",
"MixtralForCausalLM",
"AutoModelForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc136468d709f179b95 | 04c681850804e6c8 | b522e71c35912a5f | 25,000 | Unigram | null | true | true | true | true | 1 | Sequence | Sequence | Metaspace | [
"Replace",
"Replace"
] | [
"WhitespaceSplit",
"Metaspace"
] | [
"Metaspace"
] | 960 | bolbolzaban/gpt2-persian | bolbolzaban | null | 1,000 | 98,044 | False | 2022-03-02T23:29:05Z | 2021-05-21T14:23:14Z | transformers | 29 | 0 | null | text-generation | null | [
".gitattributes",
".vscode/settings.json",
"LICENSE",
"README.md",
"config.json",
"flax_model.msgpack",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 1c965e289795e1b24301cd3f4ee48e73519ac8ee | [
"transformers",
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"farsi",
"persian",
"fa",
"doi:10.57967/hf/1207",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"model_type": "gpt2", "architectures": ["GPT2LMHeadModel"], "tokenizer_config": {"bos_token": "[BOS]", "eos_token": "[EOS]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MSK]"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["farsi", "persian"]} | # GPT2-Persian
bolbolzaban/gpt2-persian is gpt2 language model that is trained with hyper parameters similar to standard gpt2-medium with following differences:
1. The context size is reduced from 1024 to 256 sub words in order to make the training affordable
2. Instead of BPE, google sentence piece tokenizor is used ... | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
66eb4e8f7f17088991d5d1fb | 848b60b6cd304b65 | ffc911e785abe60e | 151,665 | BPE | 151,387 | true | true | true | true | 22 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 15 | unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit | unsloth | {
"models": [
{
"_id": "66e98dd5899bdb384bd953b4",
"id": "Qwen/Qwen2.5-1.5B-Instruct"
}
],
"relation": "quantized"
} | 28,115 | 170,163 | False | 2024-09-18T22:05:03Z | 2025-02-06T02:17:35Z | transformers | 5 | 0 | null | text-generation | {"parameters": {"F32": 133280, "BF16": 233518592, "U8": 1351206604}, "total": 1584858476} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | d2f2dd02b071701d5100a04a7a49d6fb0bd305b7 | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"conversational",
"en",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-1.5B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
... | null | {"architectures": ["Qwen2ForCausalLM"], "model_type": "qwen2", "quantization_config": {"load_in_4bit": true, "load_in_8bit": false, "quant_method": "bitsandbytes"}, "tokenizer_config": {"bos_token": null, "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "Qwen/Qwen2.5-1.5B-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": null, "tags": ["unsloth", "transformers"]} | # Finetune Llama 3.1, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a Qwen 2.5 (all model sizes) [free Google Colab Tesla T4 notebook](https://colab.research.google.com/drive/1Kose-ucXO1IBaZq5BvbwWieuubP7hxvQ?usp=sharing).
Also a [Qwen 2.5 conversational style notebook](https://colab.research.... | null | [
"apache-2.0"
] | null | [
"en"
] | 1,584,858,476 | null | null | [
"AutoModelForCausalLM",
"Qwen2ForCausalLM",
"qwen2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65cb8b8a0b3bd8f5ce286f0c | 3271c11dab8f4183 | edc90c2ba56fad00 | 50,257 | BPE | 50,000 | false | true | true | true | 1 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 961 | ytu-ce-cosmos/turkish-gpt2-large | ytu-ce-cosmos | null | 566 | 103,737 | False | 2024-02-13T15:32:26Z | 2024-05-07T18:47:51Z | transformers | 44 | 0 | null | text-generation | {"parameters": {"F32": 774030080}, "total": 774030080} | [
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"arxiv:2404.17336",
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"endpoints_compatible",
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"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "pad_token": null, "unk_token": "<|endoftext|>"}} | {
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# turkish-gpt2
This is a Turkish GPT-2 large model. GPT-2 is designed for text generation tasks, providing the ability to continue a given text snippet in a coherent and contextually relevant manner.
Due to the diverse nature of the training data, which includes websites, bo... | null | [
"mit"
] | [
"uonlp/CulturaX"
] | [
"tr"
] | 774,030,080 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
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] | [
"text"
] | [
"text"
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674e9afe288854089127a86f | c0e1b90c863bae56 | fef4c97d7f951c6a | 131,072 | BPE | 128,810 | false | true | false | true | 2,024 | null | Sequence | ByteLevel | null | [
"Punctuation",
"ByteLevel",
"Digits"
] | [
"ByteLevel"
] | 558 | tiiuae/Falcon3-10B-Base | tiiuae | null | 4,876 | 111,675 | False | 2024-12-03T05:45:34Z | 2024-12-18T04:17:10Z | transformers | 40 | 0 | [{"name": "Falcon3-10B-Base", "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": 36.48, "name": "strict accura... | text-generation | {"parameters": {"BF16": 10305653760}, "total": 10305653760} | [
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"language": ["en", "fr", "es", "pt"], "library_name": "transformers", "license": "other", "license_name": "falcon-llm-license", "license_link": "https://falconllm.tii.ae/falcon-terms-and-conditions.html", "tags": ["falcon3"], "model-index": [{"name": "Falcon3-10B-Base", "results": [{"task": {"type": "text-generation",... | <div align="center">
<img src="https://huggingface.co/datasets/tiiuae/documentation-images/resolve/main/general/falco3-logo.png" alt="drawing" width="500"/>
</div>
# Falcon3-10B-Base
**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B parameters.
This repo... | null | [
"other",
"falcon-llm-license",
"https://falconllm.tii.ae/falcon-terms-and-conditions.html"
] | null | [
"en",
"fr",
"es",
"pt"
] | 10,305,653,760 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65b383ceef25cbaa77deb76d | 8d76fe7b80771b69 | 3f5617f282b50422 | 30,521 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 184 | LazarusNLP/all-indobert-base-v2 | LazarusNLP | null | 81 | 96,396 | False | 2024-01-26T10:05:02Z | 2024-01-26T10:48:47Z | sentence-transformers | 0 | 0 | null | sentence-similarity | {"parameters": {"F32": 124441344}, "total": 124441344} | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
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"config_sentence_transformers.json",
"model.safetensors",
"modules.json",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 5f8cb2f71a5341a1399baff98849072fc095c5c0 | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"ind",
"dataset:indonli",
"dataset:indolem/indo_story_cloze",
"dataset:unicamp-dl/mmarco",
"dataset:miracl/miracl",
"dataset:SEACrowd/wrete",
"dataset:SEACrowd/indolem_ntp",
"datase... | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["indonli", "indolem/indo_story_cloze", "unicamp-dl/mmarco", "miracl/miracl", "SEACrowd/wrete", "SEACrowd/indolem_ntp", "khalidalt/tydiqa-goldp", "SEACrowd/facqa", "indonesian-nlp/lfqa_id", "jakartaresearch/indoqa", "jakartaresearch/id-paraphrase-detection"], "eval_results": null, "lang... | # LazarusNLP/all-indobert-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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model ... | null | null | [
"indonli",
"indolem/indo_story_cloze",
"unicamp-dl/mmarco",
"miracl/miracl",
"SEACrowd/wrete",
"SEACrowd/indolem_ntp",
"khalidalt/tydiqa-goldp",
"SEACrowd/facqa",
"indonesian-nlp/lfqa_id",
"jakartaresearch/indoqa",
"jakartaresearch/id-paraphrase-detection"
] | [
"ind"
] | 124,441,344 | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
673d5220cc1ef74a34a0a917 | 64d08e5aaeb5ca63 | f7c384c23bf1ce7c | 128,257 | BPE | 280,147 | false | true | true | true | 257 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 579 | allenai/Llama-3.1-Tulu-3-8B | allenai | {
"models": [
{
"_id": "673d51e0d7c4609107c9188d",
"id": "allenai/Llama-3.1-Tulu-3-8B-DPO"
}
],
"relation": "finetune"
} | 2,765 | 291,838 | False | 2024-11-20T03:06:08Z | 2025-02-13T20:21:13Z | transformers | 178 | 0 | [{"name": "Llama-3.1-Tulu-3-8B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "IFEval (0-Shot)", "type": "wis-k/instruction-following-eval", "split": "train", "args": {"num_few_shot": 0}}, "metrics": [{"type": "inst_level_strict_acc and prompt_level_strict_acc", "valu... | text-generation | null | [
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"model.safetensors.index.json",
"notice.txt",
"special_tokens_map.json",
"toke... | 666943798adbde0b1aff34626007e26986a3c107 | [
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"safetensors",
"llama",
"text-generation",
"conversational",
"en",
"dataset:allenai/RLVR-GSM-MATH-IF-Mixed-Constraints",
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"base_model:finetune:allenai/Llama-3.1-Tulu-3-8B-DPO",
"license:llama3.1",
"model-index",
... | null | {"architectures": ["LlamaForCausalLM"], "model_type": "llama", "tokenizer_config": {"bos_token": "<|begin_of_text|>", "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{ '<|system|>\n' + message['content'] + '\n' }}{% elif message['role'] == 'user' %}{{ '<|user|>\n' + message['content'... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": ["allenai/Llama-3.1-Tulu-3-8B-DPO"], "datasets": ["allenai/RLVR-GSM-MATH-IF-Mixed-Constraints"], "language": ["en"], "library_name": "transformers", "license": "llama3.1", "pipeline_tag": "text-generation", "new_version": "allenai/Llama-3.1-Tulu-3.1-8B", "model-index": [{"name": "Llama-3.1-Tulu-3-8B", "r... | <img src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/tulu3/Tulu3-logo.png" alt="Tulu 3 banner" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Llama-3.1-Tulu-3-8B
Tülu 3 is a leading instruction following model family, offering a post-training package with fully op... | null | [
"llama3.1"
] | [
"allenai/RLVR-GSM-MATH-IF-Mixed-Constraints"
] | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
6369077ebf21b20c568aef0c | d82198b44299bcbf | 3bdf4d6ab819bf13 | 50,258 | BPE | 49,996 | false | true | true | true | 5 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 962 | DeepPavlov/rudialogpt3_medium_based_on_gpt2_v2 | DeepPavlov | null | 15,019 | 168,872 | False | 2022-11-07T13:26:22Z | 2022-11-07T14:59:03Z | transformers | 5 | 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",
"trainer_state.json",
"training_args.bin",
"vocab.json"
] | 9dfc56016728f5b7982279ab6fdd3518b923662c | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
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"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": null} | null | null | [
"other"
] | null | null | null | null | null | [
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6515e4e6c1ec63624f4c8a69 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | migtissera/SynthIA-7B-v1.3 | migtissera | null | 2,183 | 108,573 | False | 2023-09-28T20:41:10Z | 2023-11-17T21:32:09Z | transformers | 140 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"SynthIA.png",
"config.json",
"generation_config.json",
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"pytorch_model.bin.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer.model",
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] | 517a3af38e74d528c6d0b602f415a58d64982b84 | [
"transformers",
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"text-generation",
"en",
"arxiv:2306.02707",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "pad_token": null, "unk_token": "<unk>", "use_default_system_prompt": true}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["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} | SynthIA-7B-v1.3: Base model is Mistral-7B-v0.1
All SynthIA models are uncensored. Please use it with caution and with best intentions. You are responsible for how you use SynthIA.
To evoke generalized Tree of Thought + Chain of Thought reasoning, you may use the following system message:
```
Elaborate on the topic us... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"AutoModelForCausalLM",
"mistral",
"MistralForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175ef7 | 9ea605cf188ab282 | bc99105f74772a4a | 100,792 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 963 | IlyaGusev/rubertconv_toxic_clf | IlyaGusev | null | 1,110 | 101,987 | False | 2022-03-02T23:29:04Z | 2022-07-13T15:34:11Z | transformers | 15 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 39c070add685fee30cedc3a909a8a9f206d2b53d | [
"transformers",
"pytorch",
"bert",
"text-classification",
"ru",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "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": null, "eval_results": null, "language": ["ru"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text-classification"]} | # RuBERTConv Toxic Classifier
## Model description
Based on [rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model
## Intended uses & limitations
#### How to use
Colab: [link](https://colab.research.google.com/drive/1veKO9hke7myxKigZtZho_F-UM2fD9kp8)
```python... | null | [
"apache-2.0"
] | null | [
"ru"
] | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
686e7dba2ec9421e6375dc8e | 7428ef9ae5ef868f | 67da9c236fa81925 | 151,669 | BPE | 151,387 | true | true | true | true | 26 | NFC | Sequence | ByteLevel | [
"NFC"
] | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 47 | trl-internal-testing/tiny-Qwen3MoeForCausalLM | trl-internal-testing | null | 200,534 | 548,933 | False | 2025-07-09T14:33:30Z | 2025-12-19T19:11:21Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"BF16": 2574656}, "total": 2574656} | [
".gitattributes",
"README.md",
"added_tokens.json",
"chat_template.jinja",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 3d0483f76c0218a17d90d170d4dd2084882e429f | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"trl",
"conversational",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["Qwen3MoeForCausalLM"], "model_type": "qwen3_moe", "tokenizer_config": {"bos_token": null, "eos_token": "<|im_end|>", "pad_token": "<|endoftext|>", "unk_token": null}, "chat_template_jinja": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- ... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["trl"]} | # Tiny Qwen3MoeForCausalLM
This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | null | null | null | null | 2,574,656 | null | null | [
"qwen3_moe",
"AutoModelForCausalLM",
"Qwen3MoeForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
65b308d347674826d1da18e8 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | QuixiAI/WestLake-7B-v2-laser | QuixiAI | null | 7,788 | 133,203 | False | 2024-01-26T01:20:19Z | 2024-01-30T20:48:21Z | transformers | 36 | 0 | null | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
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6725ad989f0682f3f307c697 | 9f539b0447a97cc2 | f68b57645b8a1959 | 32,768 | BPE | 61,249 | true | false | true | true | 771 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 964 | UsefulSensors/moonshine-base | UsefulSensors | null | 79,543 | 236,952 | False | 2024-11-02T04:42:00Z | 2025-01-30T16:07:47Z | transformers | 41 | 0 | null | automatic-speech-recognition | {"parameters": {"F32": 61513920}, "total": 61513920} | [
".gitattributes",
"README.md",
"config.json",
"generation_config.json",
"model.safetensors",
"preprocessor_config.json",
"tokenizer.json"
] | 7a73d8d55ac0ba2ef3ae761593f6784b51f96dcf | [
"transformers",
"safetensors",
"moonshine",
"automatic-speech-recognition",
"en",
"arxiv:2410.15608",
"arxiv:1810.03993",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MoonshineForConditionalGeneration"], "model_type": "moonshine"} | {
"auto_model": "AutoModelForSpeechSeq2Seq",
"custom_class": null,
"pipeline_tag": "automatic-speech-recognition",
"processor": "AutoProcessor"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "automatic-speech-recognition", "tags": null, "arxiv": "https://arxiv.org/abs/2410.15608"} | # Moonshine
[[Blog]](https://petewarden.com/2024/10/21/introducing-moonshine-the-new-state-of-the-art-for-speech-to-text/) [[Paper]](https://arxiv.org/abs/2410.15608) [[Installation]](https://github.com/usefulsensors/moonshine/blob/main/README.md) [[Podcast]](https://notebooklm.google.com/notebook/d787d6c2-7d7b-478c-b... | null | [
"mit"
] | null | [
"en"
] | 61,513,920 | null | null | [
"AutoModelForSpeechSeq2Seq",
"MoonshineForConditionalGeneration",
"moonshine"
] | [
"automatic-speech-recognition"
] | [
"multimodal"
] | [
"audio"
] | [
"text"
] |
663c5237203472f2b50c2216 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
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] | null | [
"Replace",
"ByteFallback",
"Fuse",
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] | 88 | chihoonlee10/T3Q-ko-solar-dpo-v7.0 | chihoonlee10 | null | 6 | 95,472 | False | 2024-05-09T04:33:59Z | 2024-05-09T04:42:13Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"F16": 10731524096}, "total": 10731524096} | [
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<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated... | null | [
"apache-2.0"
] | null | null | 10,731,524,096 | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
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65bcebb144430e1870032340 | 191e06b04083279c | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
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"BertPreTokenizer"
] | [
"WordPiece"
] | 26 | ShashwatDash/finetuning-sentiment-model-3000-samples-bert-small | ShashwatDash | {
"models": [
{
"_id": "621ffdc136468d709f17ef81",
"id": "prajjwal1/bert-small"
}
],
"relation": "finetune"
} | 6 | 6 | False | 2024-02-02T13:18:41Z | 2024-02-02T13:24:45Z | transformers | 0 | 0 | [{"name": "finetuning-sentiment-model-3000-samples-bert-small", "results": []}] | text-classification | {"parameters": {"F32": 28764674}, "total": 28764674} | [
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] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
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should probably proofread and complete it, then remove this comment. -->
# finetuning-sentiment-model-3000-samples-bert-small
This model is a fine-tuned version of [prajjwal1/bert-small](https://huggingfa... | null | [
"mit"
] | null | null | 28,764,674 | null | [
"accuracy",
"f1"
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"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
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"text-classification"
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"text"
] | [
"logits"
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659117e133d72b44f0dd9d84 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | SanjiWatsuki/Sonya-7B | SanjiWatsuki | null | 691 | 99,055 | False | 2023-12-31T07:27:29Z | 2023-12-31T12:13:22Z | transformers | 33 | 0 | null | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
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"auto_model": "AutoModelForCausalLM",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["merge"]} | <div style="display: flex; justify-content: center; align-items: center">
<img src="https://huggingface.co/SanjiWatsuki/Sonya-7B/resolve/main/assets/Sonya.jpg">
</div
>
<p align="center">
<big><b>Top 1 Performer MT-bench 🤪</b></big>
</p>
## WTF is This?
Sonya-7B is, at the time of writing, the **#1 performing m... | null | [
"cc-by-4.0"
] | null | [
"en"
] | 7,241,732,096 | null | null | [
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"Metaspace"
] | [
"Metaspace"
] | 535 | bigscience/mt0-xl | bigscience | null | 742 | 104,189 | False | 2022-10-27T20:55:06Z | 2024-03-17T15:07:06Z | transformers | 32 | 0 | [{"name": "mt0-xl", "results": [{"task": {"type": "Coreference resolution"}, "dataset": {"type": "winogrande", "name": "Winogrande XL (xl)", "config": "xl", "split": "validation", "revision": "a80f460359d1e9a67c006011c94de42a8759430c"}, "metrics": [{"type": "Accuracy", "value": 52.49, "verified": false}]}, {"task": {"t... | text-generation | {"parameters": {"F32": 3742619648}, "total": 3742619648} | [
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... | null | {"architectures": ["MT5ForConditionalGeneration"], "model_type": "mt5", "tokenizer_config": {"eos_token": "</s>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
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} | {"datasets": ["bigscience/xP3", "mc4"], "language": ["af", "am", "ar", "az", "be", "bg", "bn", "ca", "ceb", "co", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fil", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "haw", "hi", "hmn", "ht", "hu", "hy", "ig", "is", "it", "iw", "ja", "jv", "ka", "kk",... | 
# Table of Contents
1. [Model Summary](#model-summary)
2. [Use](#use)
3. [Limitations](#limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
7. [Citation](#citation)
# Model Summary
> We present BLOOMZ & mT0, a ... | null | [
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... | 3,742,619,648 | null | null | [
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"Prepend",
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] | null | [
"Replace",
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"models": [
{
"_id": "654cce913a321f06c2b5ba05",
"id": "alignment-handbook/zephyr-7b-sft-full"
}
],
"relation": "finetune"
} | 180 | 95,934 | False | 2023-11-16T13:09:58Z | 2023-12-05T07:49:46Z | transformers | 123 | 0 | [{"name": "notus-7b-v1", "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", "name": "normalized accuracy", "va... | text-generation | {"parameters": {"BF16": 7241732096}, "total": 7241732096} | [
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"base_model:alignment-handbook/zephyr-7b-sft-full",
"base_model:finetune:alignment-handb... | null | {"architectures": ["MistralForCausalLM"], "model_type": "mistral", "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['conte... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": "alignment-handbook/zephyr-7b-sft-full", "datasets": ["argilla/ultrafeedback-binarized-preferences"], "language": ["en"], "library_name": "transformers", "license": "mit", "pipeline_tag": "text-generation", "tags": ["dpo", "rlaif", "preference", "ultrafeedback"], "model-index": [{"name": "notus-7b-v1", "... | <div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/60f0608166e5701b80ed3f02/dj-spsk9eXMMXVGxK6jRz.png" alt="A banner representing Notus, the wind god of the south, in a mythical and artistic style. The banner features a strong, swirling breeze, embodying the warm, wet character of th... | null | [
"mit"
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"argilla/ultrafeedback-binarized-preferences"
] | [
"en"
] | 7,241,732,096 | null | null | [
"AutoModelForCausalLM",
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"MistralForCausalLM"
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"text-generation"
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"text"
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"text"
] | [
"text"
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6500a0511e170b85744bbf39 | 83bf28f8b6767a2f | ae88e903e2b563a1 | 50,295 | BPE | 50,000 | false | true | true | true | 39 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 85 | jphme/phi-1_5_Wizard_Vicuna_uncensored | jphme | null | 21 | 95,252 | False | 2023-09-12T17:30:57Z | 2023-09-21T12:23:23Z | transformers | 27 | 0 | null | text-generation | null | [
"README.md",
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} | {"base_model": null, "datasets": ["ehartford/wizard_vicuna_70k_unfiltered"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["pytorch", "phi", "phi-1_5"... | # Phi 1.5 Wizard Vicuna Experimental
Experimental Finetune on Microsoft's [Phi 1.5](https://huggingface.co/microsoft/phi-1_5).
This is highly experimental, only trained on a subset of the 70k Wizard Vicuna dataset and not meant for production use.
This model also runs reasonably fast on CPU!
Will update with later ... | null | null | [
"ehartford/wizard_vicuna_70k_unfiltered"
] | [
"en"
] | null | null | null | [
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] | 130 | hyunseoki/ko-ref-llama2-13b | hyunseoki | null | 782 | 99,428 | False | 2023-10-04T06:38:18Z | 2023-10-04T07:03:44Z | transformers | 1 | 0 | null | text-generation | null | [
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] | 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-ref-llama2-13b is an auto-regressive language model based on the LLaMA2 transformer architecture.
**Base Model**
Llama-2-13B
**Training D... | null | null | null | [
"ko"
] | null | null | null | [
"AutoModelForCausalLM",
"llama",
"LlamaForCausalLM"
] | [
"text-generation"
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"text"
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"text"
] | [
"text"
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64d98b40931837e433cd838d | e13e27192dde8df0 | 7ce118731980e5c6 | 29,794 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
] | [
"BertPreTokenizer"
] | [
"WordPiece"
] | 291 | Nelci/bertimbau_hate_speech | Nelci | {
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"_id": "621ffdc136468d709f17e62a",
"id": "neuralmind/bert-large-portuguese-cased"
}
],
"relation": "finetune"
} | 16 | 95,159 | False | 2023-08-14T02:02:40Z | 2023-08-17T04:12:32Z | transformers | 3 | 0 | [{"name": "bertimbau_hate_speech", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "hate_speech_portuguese", "type": "hate_speech_portuguese", "config": "default", "split": "train", "args": "default"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value":... | text-classification | {"parameters": {"F32": 334398466}, "total": 334398466} | [
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"pipeline_tag": "text-classification",
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} | {"base_model": "neuralmind/bert-large-portuguese-cased", "datasets": ["hate_speech_portuguese"], "license": "mit", "metrics": ["accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "bertimbau_hate_speech", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset"... | <!-- 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. -->
# bertimbau_hate_speech
This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neura... | null | [
"mit"
] | [
"hate_speech_portuguese"
] | null | 334,398,466 | null | [
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
6667c68efd578080e1411819 | 88cd37e502d27a0a | 0e7bc0977f200d1c | 32,000 | BPE | 58,980 | true | false | true | true | 3 | Sequence | null | Sequence | [
"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 88 | DAMO-NLP-SG/VideoLLaMA2-7B | DAMO-NLP-SG | null | 490 | 106,587 | False | 2024-06-11T03:37:50Z | 2024-08-13T15:15:28Z | transformers | 42 | 0 | null | visual-question-answering | {"parameters": {"BF16": 8034428160}, "total": 8034428160} | [
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} | {"base_model": null, "datasets": ["OpenGVLab/VideoChat2-IT", "Lin-Chen/ShareGPT4V", "liuhaotian/LLaVA-Instruct-150K"], "eval_results": null, "language": ["en"], "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "pipeline_tag... | <p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/63913b120cf6b11c487ca31d/ROs4bHIp4zJ7g7vzgUycu.png" width="150" style="margin-bottom: 0.2;"/>
<p>
<h3 align="center"><a href="https://arxiv.org/abs/2406.07476">VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understandi... | null | [
"apache-2.0"
] | [
"OpenGVLab/VideoChat2-IT",
"Lin-Chen/ShareGPT4V",
"liuhaotian/LLaVA-Instruct-150K"
] | [
"en"
] | 8,034,428,160 | null | [
"accuracy"
] | [
"AutoModelForCausalLM",
"Videollama2MistralForCausalLM",
"videollama2_mistral"
] | [
"visual-question-answering",
"text-generation"
] | [
"text",
"multimodal"
] | [
"text",
"image"
] | [
"logits",
"text"
] |
62561ec5d444a9b5a0ea9a5a | 83bf28f8b6767a2f | ae88e903e2b563a1 | 50,295 | BPE | 50,000 | false | true | true | true | 39 | null | ByteLevel | ByteLevel | null | [
"ByteLevel"
] | [
"ByteLevel"
] | 85 | Salesforce/codegen-16B-mono | Salesforce | null | 223 | 95,815 | False | 2022-04-13T00:52:21Z | 2025-01-31T21:27:22Z | transformers | 126 | 0 | null | text-generation | null | [
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] | 88d4d599ddeb60b0320baaba7e868009efb3e1e2 | [
"transformers",
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"codegen",
"text-generation",
"arxiv:2203.13474",
"license:bsd-3-clause",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["CodeGenForCausalLM"], "model_type": "codegen", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "bsd-3-clause", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # CodeGen (CodeGen-Mono 16B)
## Model description
CodeGen is a family of autoregressive language models for **program synthesis** from the paper: [A Conversational Paradigm for Program Synthesis](https://arxiv.org/abs/2203.13474) by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savar... | null | [
"bsd-3-clause"
] | null | null | null | null | null | [
"AutoModelForCausalLM",
"codegen",
"CodeGenForCausalLM"
] | [
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"text"
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6434f6425408e9c12a015301 | 58967ba68263f0aa | 2f8d5857ae5fa330 | 50,277 | BPE | 50,009 | true | true | true | true | 25 | NFC | ByteLevel | ByteLevel | [
"NFC"
] | [
"ByteLevel"
] | [
"ByteLevel"
] | 86 | stabilityai/stablelm-base-alpha-7b | stabilityai | null | 2,547 | 103,174 | False | 2023-04-11T05:55:14Z | 2023-10-19T04:59:17Z | transformers | 208 | 0 | null | text-generation | null | [
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"... | 1d43a3b40d7d708d8084d07dfae0c4e9fd95c04f | [
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"en",
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"text-generation-inference",
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] | null | {"architectures": ["GPTNeoXForCausalLM"], "model_type": "gpt_neox", "tokenizer_config": {"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
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"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"
] | [
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6894dcf7bdef683991886a0a | 441f36ff7235b58e | 985b920c8f6b14f1 | 200,019 | BPE | 446,189 | false | true | true | true | 21 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 54 | unsloth/gpt-oss-120b-unsloth-bnb-4bit | unsloth | {
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{
"_id": "68913522f16f3c8aaffccf1f",
"id": "openai/gpt-oss-120b"
}
],
"relation": "quantized"
} | 28,928 | 210,634 | False | 2025-08-07T17:05:59Z | 2025-08-08T08:40:15Z | transformers | 15 | 0 | null | text-generation | {"parameters": {"F32": 9818640, "F16": 1211645952, "U8": 119233530114}, "total": 116829156672} | [
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} | {"base_model": ["openai/gpt-oss-120b"], "datasets": null, "eval_results": null, "language": null, "library_name": "transformers", "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["openai", "unsloth"]} | null | null | [
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66320d646aee5b05e4b055f3 | 803e3c8528c55bf1 | a1f1bd381dcb9329 | 128,256 | BPE | 280,147 | false | true | true | true | 256 | null | Sequence | ByteLevel | null | [
"Split",
"ByteLevel"
] | [
"ByteLevel"
] | 352 | MaziyarPanahi/Llama-3-8B-Instruct-v0.4 | MaziyarPanahi | {
"models": [
{
"_id": "661f97d0b00f5f1f620c4f25",
"id": "meta-llama/Meta-Llama-3-8B-Instruct"
}
],
"relation": "finetune"
} | 664 | 98,563 | False | 2024-05-01T09:37:40Z | 2024-05-04T18:05:56Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"BF16": 8030261248}, "total": 8030261248} | [
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# Llama-3-8B-Instruct-v0.4
This model was developed based on `meta-llama/Meta-Llama-3-8B-Instruct` model.
# Quantized GGUF
All GGUF models are available here: [MaziyarPanahi/Llama-3-... | null | [
"other",
"llama3",
"LICENSE"
] | null | [
"en"
] | 8,030,261,248 | null | null | [
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"Prepend",
"Replace"
] | null | [
"Replace",
"ByteFallback",
"Fuse",
"Strip"
] | 46 | pankajmathur/model_007 | pankajmathur | null | 1,718 | 103,962 | False | 2023-08-05T04:15:55Z | 2025-03-17T15:16:30Z | transformers | 21 | 0 | [{"name": "model_007", "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": 71.08, "name": "normalized ... | text-generation | {"parameters": {"F16": 68976648192}, "total": 68976648192} | [
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"dataset:ehartford/dolphin",
"arxiv:2306.02707",
"license:l... | 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",
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"datasets": ["pankajmathur/orca_mini_v1_dataset", "pankajmathur/dolly-v2_orca", "pankajmathur/WizardLM_Orca", "pankajmathur/alpaca_orca", "ehartford/dolphin"], "language": ["en"], "library_name": "transformers", "license": "llama2", "model-index": [{"name": "model_007", "results": [{"task": {"type": "text-generation",... | # model_007
A hybrid (explain + instruct) style Llama2-70b model, Pleae check examples below for both style prompts, Here is the list of datasets used:
* Open-Platypus
* Alpaca
* WizardLM
* Dolly-V2
* Dolphin Samples (~200K)
* Orca_minis_v1
* Alpaca_orca
* WizardLM_orca
* Dolly-V2_orca
<br>
**P.S. If you're intere... | null | [
"llama2"
] | [
"pankajmathur/orca_mini_v1_dataset",
"pankajmathur/dolly-v2_orca",
"pankajmathur/WizardLM_Orca",
"pankajmathur/alpaca_orca",
"ehartford/dolphin"
] | [
"en"
] | 68,976,648,192 | null | null | [
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"text"
] | [
"text"
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6617f0c145a34bdf338e1484 | 53ecf467267e2824 | 535fa14da0af647c | 30,522 | WordPiece | null | true | true | true | true | 5 | BertNormalizer | BertPreTokenizer | WordPiece | [
"BertNormalizer"
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"WordPiece"
] | 0 | protectai/vishnun-codenlbert-sm-onnx | protectai | {
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}
],
"relation": "quantized"
} | 1,015 | 100,915 | False | 2024-04-11T14:16:33Z | 2024-04-26T06:13:10Z | transformers | 1 | 0 | null | text-classification | null | [
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"license:apache-2.0",
"text-embeddings-inference",
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] | 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": "vishnun/codenlbert-sm", "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-classification", "tags": null, "inference": false} | # ONNX version of vishnun/codenlbert-sm
**This model is a conversion of [vishnun/codenlbert-sm](https://huggingface.co/vishnun/codenlbert-sm) to ONNX** format using the [🤗 Optimum](https://huggingface.co/docs/optimum/index) library. | null | [
"apache-2.0"
] | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
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