license: llama3.1
library_name: transformers
tags:

• mergekit
• merge
  base_model:
• meta-llama/Meta-Llama-3.1-8B-Instruct
• grimjim/Llama-3-Instruct-abliteration-LoRA-8B
  pipeline_tag: text-generation
  model-index:
• name: Llama-3.1-8B-Instruct-abliterated_via_adapter
  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: 48.7
      name: strict accuracy
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter
      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: 29.42
      name: normalized accuracy
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter
      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: 12.39
      name: exact match
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter
      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: 8.5
      name: acc_norm
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter
      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: 9.26
      name: acc_norm
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter
      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: 29.46
      name: accuracy
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter
      name: Open LLM Leaderboard

Llama-3.1-8B-Instruct-abliterated_via_adapter

This model is a merge of pre-trained language models created using mergekit.

A LoRA was applied to "abliterate" refusals in meta-llama/Meta-Llama-3.1-8B-Instruct. The result appears to work despite the LoRA having been derived from Llama 3 instead of Llama 3.1, which implies that there is significant feature commonality between the 3 and 3.1 models.

The LoRA was extracted from failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 using meta-llama/Meta-Llama-3-8B-Instruct as a base.

Built with Llama.

Merge Details

Merge Method

This model was merged using the task arithmetic merge method using meta-llama/Meta-Llama-3.1-8B-Instruct + grimjim/Llama-3-Instruct-abliteration-LoRA-8B as a base.

Configuration

The following YAML configuration was used to produce this model:

base_model: meta-llama/Meta-Llama-3.1-8B-Instruct+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
dtype: bfloat16
merge_method: task_arithmetic
parameters:
  normalize: false
slices:
- sources:
  - layer_range: [0, 32]
    model: meta-llama/Meta-Llama-3.1-8B-Instruct+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
    parameters:
      weight: 1.0

Open LLM Leaderboard Evaluation Results

Detailed results can be found here