README.md

metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - netcat420/MFANNv0.21.11
  - mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
model-index:
  - name: MFANN-llama3.1-Abliterated-SLERP
    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: 25.91
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=netcat420/MFANN-llama3.1-Abliterated-SLERP
          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: 22.28
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=netcat420/MFANN-llama3.1-Abliterated-SLERP
          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: 4.53
            name: exact match
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=netcat420/MFANN-llama3.1-Abliterated-SLERP
          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: 3.13
            name: acc_norm
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=netcat420/MFANN-llama3.1-Abliterated-SLERP
          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: 5.71
            name: acc_norm
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=netcat420/MFANN-llama3.1-Abliterated-SLERP
          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: 21.42
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=netcat420/MFANN-llama3.1-Abliterated-SLERP
          name: Open LLM Leaderboard

merge

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

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

• netcat420/MFANNv0.21.11
• mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
        layer_range: [0, 32]
      - model: netcat420/MFANNv0.21.11
        layer_range: [0, 32]
merge_method: slerp
base_model: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	13.83
IFEval (0-Shot)	25.91
BBH (3-Shot)	22.28
MATH Lvl 5 (4-Shot)	4.53
GPQA (0-shot)	3.13
MuSR (0-shot)	5.71
MMLU-PRO (5-shot)	21.42