richarderkhov/nbeerbower_-_mistral-nemo-cc-12b-gguf overview

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    "summary": "nbeerbower/mistral-nemo-gutenberg-12B-v3 finetuned on flammenai/casual-conversation-DPO. This is an experimental finetune that formats the conversation data sequentially with ChatML. ### Method Finetuned using an A100 on Google Colab for 3 epochs. Fine-tune Llama 3 with ORPO # Open LLM Leaderboard Evaluation Results Detailed results can be found here |      Metric       |Value| |-------------------|----:| |Avg.               |17.08| |IFEval (0-Shot)    |14.35| |BBH (3-Shot)       |34.45| |MATH Lvl 5 (4-Shot)| 1.81| |GPQA (0-shot)      | 8.72| |MuSR (0-shot)      |14.26| |MMLU-PRO (5-shot)  |28.87|",
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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\nmistral-nemo-cc-12B - GGUF\n- Model creator: https://huggingface.co/nbeerbower/\n- Original model: https://huggingface.co/nbeerbower/mistral-nemo-cc-12B/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [mistral-nemo-cc-12B.Q2_K.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q2_K.gguf) | Q2_K | 4.46GB |\n| [mistral-nemo-cc-12B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.IQ3_XS.gguf) | IQ3_XS | 4.94GB |\n| [mistral-nemo-cc-12B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.IQ3_S.gguf) | IQ3_S | 5.18GB |\n| [mistral-nemo-cc-12B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q3_K_S.gguf) | Q3_K_S | 5.15GB |\n| [mistral-nemo-cc-12B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.IQ3_M.gguf) | IQ3_M | 5.33GB |\n| [mistral-nemo-cc-12B.Q3_K.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q3_K.gguf) | Q3_K | 5.67GB |\n| [mistral-nemo-cc-12B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q3_K_M.gguf) | Q3_K_M | 5.67GB |\n| [mistral-nemo-cc-12B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q3_K_L.gguf) | Q3_K_L | 6.11GB |\n| [mistral-nemo-cc-12B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.IQ4_XS.gguf) | IQ4_XS | 6.33GB |\n| [mistral-nemo-cc-12B.Q4_0.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q4_0.gguf) | Q4_0 | 6.59GB |\n| [mistral-nemo-cc-12B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.IQ4_NL.gguf) | IQ4_NL | 6.65GB |\n| [mistral-nemo-cc-12B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q4_K_S.gguf) | Q4_K_S | 6.63GB |\n| [mistral-nemo-cc-12B.Q4_K.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q4_K.gguf) | Q4_K | 6.96GB |\n| [mistral-nemo-cc-12B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q4_K_M.gguf) | Q4_K_M | 6.96GB |\n| [mistral-nemo-cc-12B.Q4_1.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q4_1.gguf) | Q4_1 | 7.26GB |\n| [mistral-nemo-cc-12B.Q5_0.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q5_0.gguf) | Q5_0 | 7.93GB |\n| [mistral-nemo-cc-12B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q5_K_S.gguf) | Q5_K_S | 7.93GB |\n| [mistral-nemo-cc-12B.Q5_K.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q5_K.gguf) | Q5_K | 8.13GB |\n| [mistral-nemo-cc-12B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q5_K_M.gguf) | Q5_K_M | 8.13GB |\n| [mistral-nemo-cc-12B.Q5_1.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q5_1.gguf) | Q5_1 | 8.61GB |\n| [mistral-nemo-cc-12B.Q6_K.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q6_K.gguf) | Q6_K | 9.37GB |\n| [mistral-nemo-cc-12B.Q8_0.gguf](https://huggingface.co/RichardErkhov/nbeerbower_-_mistral-nemo-cc-12B-gguf/blob/main/mistral-nemo-cc-12B.Q8_0.gguf) | Q8_0 | 12.13GB |\n\n\n\n\nOriginal model description:\n---\nlicense: apache-2.0\nlibrary_name: transformers\nbase_model:\n- nbeerbower/mistral-nemo-gutenberg-12B-v3\ndatasets:\n- flammenai/casual-conversation-DPO\nmodel-index:\n- name: mistral-nemo-cc-12B\n  results:\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: IFEval (0-Shot)\n      type: HuggingFaceH4/ifeval\n      args:\n        num_few_shot: 0\n    metrics:\n    - type: inst_level_strict_acc and prompt_level_strict_acc\n      value: 14.35\n      name: strict accuracy\n    source:\n      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/mistral-nemo-cc-12B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: BBH (3-Shot)\n      type: BBH\n      args:\n        num_few_shot: 3\n    metrics:\n    - type: acc_norm\n      value: 34.45\n      name: normalized accuracy\n    source:\n      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/mistral-nemo-cc-12B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: MATH Lvl 5 (4-Shot)\n      type: hendrycks/competition_math\n      args:\n        num_few_shot: 4\n    metrics:\n    - type: exact_match\n      value: 1.81\n      name: exact match\n    source:\n      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/mistral-nemo-cc-12B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: GPQA (0-shot)\n      type: Idavidrein/gpqa\n      args:\n        num_few_shot: 0\n    metrics:\n    - type: acc_norm\n      value: 8.72\n      name: acc_norm\n    source:\n      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/mistral-nemo-cc-12B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: MuSR (0-shot)\n      type: TAUR-Lab/MuSR\n      args:\n        num_few_shot: 0\n    metrics:\n    - type: acc_norm\n      value: 14.26\n      name: acc_norm\n    source:\n      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/mistral-nemo-cc-12B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: MMLU-PRO (5-shot)\n      type: TIGER-Lab/MMLU-Pro\n      config: main\n      split: test\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 28.87\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/mistral-nemo-cc-12B\n      name: Open LLM Leaderboard\n---\n\n# mistral-nemo-cc-12B\n\n[nbeerbower/mistral-nemo-gutenberg-12B-v3](https://huggingface.co/nbeerbower/mistral-nemo-gutenberg-12B-v3) finetuned on [flammenai/casual-conversation-DPO](https://huggingface.co/datasets/flammenai/casual-conversation-DPO).\n\nThis is an experimental finetune that formats the conversation data sequentially with ChatML.\n\n### Method\n\nFinetuned using an A100 on Google Colab for 3 epochs.\n\n[Fine-tune Llama 3 with ORPO](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html)\n# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)\nDetailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_nbeerbower__mistral-nemo-cc-12B)\n\n|      Metric       |Value|\n|-------------------|----:|\n|Avg.               |17.08|\n|IFEval (0-Shot)    |14.35|\n|BBH (3-Shot)       |34.45|\n|MATH Lvl 5 (4-Shot)| 1.81|\n|GPQA (0-shot)      | 8.72|\n|MuSR (0-shot)      |14.26|\n|MMLU-PRO (5-shot)  |28.87|\n\n\n\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
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  "last_modified": "2024-09-28T02:36:13.000Z",
  "created_at": "2024-09-27T22:59:46.000Z",
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