richarderkhov/mlabonne_-_omnibeagle-7b-gguf overview

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    "summary": "OmniBeagle-7B is a merge of the following models using LazyMergekit: * shadowml/BeagleSempra-7B * shadowml/BeagSake-7B * shadowml/WestBeagle-7B",
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    "readme_markdown": "Quantization made by Richard Erkhov.\n\n[Github](https://github.com/RichardErkhov)\n\n[Discord](https://discord.gg/pvy7H8DZMG)\n\n[Request more models](https://github.com/RichardErkhov/quant_request)\n\n\nOmniBeagle-7B - GGUF\n- Model creator: https://huggingface.co/mlabonne/\n- Original model: https://huggingface.co/mlabonne/OmniBeagle-7B/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [OmniBeagle-7B.Q2_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q2_K.gguf) | Q2_K | 2.53GB |\n| [OmniBeagle-7B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.IQ3_XS.gguf) | IQ3_XS | 2.81GB |\n| [OmniBeagle-7B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.IQ3_S.gguf) | IQ3_S | 2.96GB |\n| [OmniBeagle-7B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q3_K_S.gguf) | Q3_K_S | 2.95GB |\n| [OmniBeagle-7B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.IQ3_M.gguf) | IQ3_M | 3.06GB |\n| [OmniBeagle-7B.Q3_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q3_K.gguf) | Q3_K | 3.28GB |\n| [OmniBeagle-7B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q3_K_M.gguf) | Q3_K_M | 3.28GB |\n| [OmniBeagle-7B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q3_K_L.gguf) | Q3_K_L | 3.56GB |\n| [OmniBeagle-7B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.IQ4_XS.gguf) | IQ4_XS | 3.67GB |\n| [OmniBeagle-7B.Q4_0.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q4_0.gguf) | Q4_0 | 3.83GB |\n| [OmniBeagle-7B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.IQ4_NL.gguf) | IQ4_NL | 3.87GB |\n| [OmniBeagle-7B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q4_K_S.gguf) | Q4_K_S | 3.86GB |\n| [OmniBeagle-7B.Q4_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q4_K.gguf) | Q4_K | 4.07GB |\n| [OmniBeagle-7B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q4_K_M.gguf) | Q4_K_M | 4.07GB |\n| [OmniBeagle-7B.Q4_1.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q4_1.gguf) | Q4_1 | 4.24GB |\n| [OmniBeagle-7B.Q5_0.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q5_0.gguf) | Q5_0 | 4.65GB |\n| [OmniBeagle-7B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q5_K_S.gguf) | Q5_K_S | 4.65GB |\n| [OmniBeagle-7B.Q5_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q5_K.gguf) | Q5_K | 4.78GB |\n| [OmniBeagle-7B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q5_K_M.gguf) | Q5_K_M | 4.78GB |\n| [OmniBeagle-7B.Q5_1.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q5_1.gguf) | Q5_1 | 5.07GB |\n| [OmniBeagle-7B.Q6_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q6_K.gguf) | Q6_K | 5.53GB |\n| [OmniBeagle-7B.Q8_0.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_OmniBeagle-7B-gguf/blob/main/OmniBeagle-7B.Q8_0.gguf) | Q8_0 | 7.17GB |\n\n\n\n\nOriginal model description:\n---\nlicense: cc-by-nc-4.0\ntags:\n- merge\n- mergekit\n- lazymergekit\nbase_model:\n- shadowml/BeagleSempra-7B\n- shadowml/BeagSake-7B\n- shadowml/WestBeagle-7B\nmodel-index:\n- name: OmniBeagle-7B\n  results:\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: AI2 Reasoning Challenge (25-Shot)\n      type: ai2_arc\n      config: ARC-Challenge\n      split: test\n      args:\n        num_few_shot: 25\n    metrics:\n    - type: acc_norm\n      value: 72.61\n      name: normalized accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/OmniBeagle-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: HellaSwag (10-Shot)\n      type: hellaswag\n      split: validation\n      args:\n        num_few_shot: 10\n    metrics:\n    - type: acc_norm\n      value: 88.93\n      name: normalized accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/OmniBeagle-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: MMLU (5-Shot)\n      type: cais/mmlu\n      config: all\n      split: test\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 64.8\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/OmniBeagle-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: TruthfulQA (0-shot)\n      type: truthful_qa\n      config: multiple_choice\n      split: validation\n      args:\n        num_few_shot: 0\n    metrics:\n    - type: mc2\n      value: 74.45\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/OmniBeagle-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: Winogrande (5-shot)\n      type: winogrande\n      config: winogrande_xl\n      split: validation\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 83.11\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/OmniBeagle-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: GSM8k (5-shot)\n      type: gsm8k\n      config: main\n      split: test\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 70.05\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/OmniBeagle-7B\n      name: Open LLM Leaderboard\n---\n\n# OmniBeagle-7B\n\nOmniBeagle-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):\n* [shadowml/BeagleSempra-7B](https://huggingface.co/shadowml/BeagleSempra-7B)\n* [shadowml/BeagSake-7B](https://huggingface.co/shadowml/BeagSake-7B)\n* [shadowml/WestBeagle-7B](https://huggingface.co/shadowml/WestBeagle-7B)\n\n## 🧩 Configuration\n\n```yaml\nmodels:\n  - model: mistralai/Mistral-7B-v0.1\n    # no parameters necessary for base model\n  - model: shadowml/BeagleSempra-7B\n    parameters:\n      density: 0.65\n      weight: 0.4\n  - model: shadowml/BeagSake-7B\n    parameters:\n      density: 0.6\n      weight: 0.35\n  - model: shadowml/WestBeagle-7B\n    parameters:\n      density: 0.6\n      weight: 0.35\nmerge_method: dare_ties\nbase_model: mistralai/Mistral-7B-v0.1\nparameters:\n  int8_mask: true\ndtype: float16\n```\n\n## 💻 Usage\n\n```python\n!pip install -qU transformers accelerate\n\nfrom transformers import AutoTokenizer\nimport transformers\nimport torch\n\nmodel = \"mlabonne/OmniBeagle-7B\"\nmessages = [{\"role\": \"user\", \"content\": \"What is a large language model?\"}]\n\ntokenizer = AutoTokenizer.from_pretrained(model)\nprompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\npipeline = transformers.pipeline(\n    \"text-generation\",\n    model=model,\n    torch_dtype=torch.float16,\n    device_map=\"auto\",\n)\n\noutputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)\nprint(outputs[0][\"generated_text\"])\n```\n# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)\nDetailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__OmniBeagle-7B)\n\n|             Metric              |Value|\n|---------------------------------|----:|\n|Avg.                             |75.66|\n|AI2 Reasoning Challenge (25-Shot)|72.61|\n|HellaSwag (10-Shot)              |88.93|\n|MMLU (5-Shot)                    |64.80|\n|TruthfulQA (0-shot)              |74.45|\n|Winogrande (5-shot)              |83.11|\n|GSM8k (5-shot)                   |70.05|\n\n\n\n",
    "related_quantizations": []
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  "tags": [
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