README.md

metadata

language:
  - en
license: mit
base_model:
  - mistralai/Mistral-7B-v0.1
datasets:
  - argilla/ultrafeedback-binarized-preferences-cleaned
pipeline_tag: text-generation
model-index:
  - name: Mistral-ORPO-β
    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
            value: 61.18
        source:
          name: Open LLM Leaderboard
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaist-ai%2Fmistral-orpo-beta
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            name: normalized accuracy
            value: 84.03
        source:
          name: Open LLM Leaderboard
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaist-ai%2Fmistral-orpo-beta
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 47.69
        source:
          name: Open LLM Leaderboard
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaist-ai%2Fmistral-orpo-beta
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            name: accuracy
            value: 39.8
        source:
          name: Open LLM Leaderboard
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaist-ai%2Fmistral-orpo-beta
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            name: accuracy
            value: 63.26
        source:
          name: Open LLM Leaderboard
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaist-ai%2Fmistral-orpo-beta
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            name: accuracy
            value: 79.24
        source:
          name: Open LLM Leaderboard
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaist-ai%2Fmistral-orpo-beta
      - task:
          type: text-generation
        dataset:
          name: AlpacaEval 1
          type: AlpacaEval
        metrics:
          - type: AlpacaEval 1.0
            value: 91.16%
            name: Win Rate
        source:
          url: https://tatsu-lab.github.io/alpaca_eval/
          name: Leaderboard
      - task:
          type: text-generation
        dataset:
          name: AlpacaEval 2
          type: AlpacaEval
        metrics:
          - type: AlpacaEval 2.0
            value: 12.57%
            name: Win Rate
        source:
          url: https://tatsu-lab.github.io/alpaca_eval/
          name: Leaderboard
      - task:
          type: text-generation
        dataset:
          name: MT-Bench
          type: MT-Bench
        metrics:
          - type: MT-Bench
            value: 7.322
            name: Score
        source:
          url: https://github.com/lm-sys/FastChat/blob/main/fastchat/llm_judge/
          name: self-reported
quantized_by: bartowski

Llamacpp Quantizations of mistral-orpo-beta

Using llama.cpp release b2440 for quantization.

Original model: https://huggingface.co/kaist-ai/mistral-orpo-beta

Download a file (not the whole branch) from below:

Filename	Quant type	File Size	Description
mistral-orpo-beta-Q8_0.gguf	Q8_0	7.69GB	Extremely high quality, generally unneeded but max available quant.
mistral-orpo-beta-Q6_K.gguf	Q6_K	5.94GB	Very high quality, near perfect, recommended.
mistral-orpo-beta-Q5_K_M.gguf	Q5_K_M	5.13GB	High quality, very usable.
mistral-orpo-beta-Q5_K_S.gguf	Q5_K_S	4.99GB	High quality, very usable.
mistral-orpo-beta-Q5_0.gguf	Q5_0	4.99GB	High quality, older format, generally not recommended.
mistral-orpo-beta-Q4_K_M.gguf	Q4_K_M	4.36GB	Good quality, similar to 4.25 bpw.
mistral-orpo-beta-Q4_K_S.gguf	Q4_K_S	4.14GB	Slightly lower quality with small space savings.
mistral-orpo-beta-Q4_0.gguf	Q4_0	4.10GB	Decent quality, older format, generally not recommended.
mistral-orpo-beta-Q3_K_L.gguf	Q3_K_L	3.82GB	Lower quality but usable, good for low RAM availability.
mistral-orpo-beta-Q3_K_M.gguf	Q3_K_M	3.51GB	Even lower quality.
mistral-orpo-beta-Q3_K_S.gguf	Q3_K_S	3.16GB	Low quality, not recommended.
mistral-orpo-beta-Q2_K.gguf	Q2_K	2.71GB	Extremely low quality, not recommended.

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