license: llama3.1
library_name: transformers
tags:

• abliterated
• uncensored
• autoquant
• gguf
  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

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