ZEUS-8B-V25

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

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using unsloth/Meta-Llama-3.1-8B-Instruct as a base.

Models Merged

The following models were included in the merge:

• arcee-ai/Llama-3.1-SuperNova-Lite
• Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
• unsloth/Llama-3.1-Storm-8B
• output\strawberry-patch
• VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct

Configuration

The following YAML configuration was used to produce this model:

base_model: unsloth/Meta-Llama-3.1-8B-Instruct
dtype: bfloat16
merge_method: dare_ties
parameters:
  int8_mask: 1.0
  normalize: 1.0
  random_seed: 145.0
slices:
- sources:
  - layer_range: [0, 32]
    model: unsloth/Llama-3.1-Storm-8B
    parameters:
      density: 0.94
      weight: 0.35
  - layer_range: [0, 32]
    model: arcee-ai/Llama-3.1-SuperNova-Lite
    parameters:
      density: 0.92
      weight: 0.2
  - layer_range: [0, 32]
    model: VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct
    parameters:
      density: 0.91
      weight: 0.2
  - layer_range: [0, 32]
    model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
    parameters:
      density: 0.93
      weight: 0.19
  - layer_range: [0, 32]
    model: output\strawberry-patch
    parameters:
      density: 0.92
      weight: 0.06
  - layer_range: [0, 32]
    model: unsloth/Meta-Llama-3.1-8B-Instruct
tokenizer:
  tokens:
    <|begin_of_text|>:
      force: true
      source: unsloth/Meta-Llama-3.1-8B-Instruct
    <|eot_id|>:
      force: true
      source: unsloth/Meta-Llama-3.1-8B-Instruct
    <|finetune_right_pad_id|>:
      force: true
      source: unsloth/Meta-Llama-3.1-8B-Instruct
    pad_token:
      force: true
      source:
        kind: model_token
        model: unsloth/Meta-Llama-3.1-8B-Instruct
        token_id: 128004

Open LLM Leaderboard Evaluation Results

Detailed results can be found here! Summarized results can be found here!

Metric	Value (%)
Average	15.00
IFEval (0-Shot)	33.20
BBH (3-Shot)	21.85
MATH Lvl 5 (4-Shot)	9.52
GPQA (0-shot)	1.90
MuSR (0-shot)	2.60
MMLU-PRO (5-shot)	20.94