metadata

license: llama3.1
library_name: transformers
tags:
  - abliterated
  - uncensored
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
model-index:
  - name: Meta-Llama-3.1-8B-Instruct-abliterated
    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: 73.29
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 27.13
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 6.42
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 0.89
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 3.21
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 27.81
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
          name: Open LLM Leaderboard

🦙 Meta-Llama-3.1-8B-Instruct-abliterated

🦙 Llama 3.1 70B Instruct lorablated

This is an uncensored version of Llama 3.1 8B Instruct created with abliteration (see this article to know more about it).

Special thanks to @FailSpy for the original code and technique. Please follow him if you're interested in abliterated models.

⚡️ Quantization

Thanks to ZeroWw and Apel-sin for the quants.

New GGUF: https://huggingface.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF
ZeroWw GGUF: https://huggingface.co/ZeroWw/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF
EXL2: https://huggingface.co/Apel-sin/llama-3.1-8B-abliterated-exl2

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	23.13
IFEval (0-Shot)	73.29
BBH (3-Shot)	27.13
MATH Lvl 5 (4-Shot)	6.42
GPQA (0-shot)	0.89
MuSR (0-shot)	3.21
MMLU-PRO (5-shot)	27.81