djuna/L3.1-Suze-Vume-calc

merge

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

Merge Details

Merge Method

This model was merged using the linear DARE merge method using Orenguteng/Llama-3.1-8B-Lexi-Uncensored as a base.

Models Merged

The following models were included in the merge:

• djuna/L3-Suze-Vume

Configuration

The following YAML configuration was used to produce this model:

merge_method: dare_linear
models:
  - model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored
    parameters:
      weight:
        - filter: v_proj
          value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
        - filter: o_proj
          value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
        - filter: up_proj
          value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
        - filter: gate_proj
          value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
        - filter: down_proj
          value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
        - value: 1
  - model: djuna/L3-Suze-Vume
    parameters:
      weight:
        - filter: v_proj
          value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
        - filter: o_proj
          value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
        - filter: up_proj
          value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
        - filter: gate_proj
          value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
        - filter: down_proj
          value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
        - value: 0
base_model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored
tokenizer_source: base
dtype: float32
out_dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	25.75
IFEval (0-Shot)	72.97
BBH (3-Shot)	31.14
MATH Lvl 5 (4-Shot)	9.89
GPQA (0-shot)	4.25
MuSR (0-shot)	8.30
MMLU-PRO (5-shot)	27.94