metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - akjindal53244/Llama-3.1-Storm-8B
  - Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
  - arcee-ai/Llama-3.1-SuperNova-Lite
  - unsloth/Meta-Llama-3.1-8B-Instruct
model-index:
  - name: ZEUS-8B-V10
    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: 77.07
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/ZEUS-8B-V10
          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: 32.7
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/ZEUS-8B-V10
          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: 20.09
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/ZEUS-8B-V10
          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: 9.96
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/ZEUS-8B-V10
          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: 9.09
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/ZEUS-8B-V10
          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: 32.26
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/ZEUS-8B-V10
          name: Open LLM Leaderboard

ZEUS 8B V10

A simple V2 recreation with a few changes:

Unified tokenizer (no noticeable changes)
Using int_mask and normalize (the latter being enabled by default in mergekit)
Using a preset seed to create a reproducible config (due to DARE relying on RNG)

Expecting little to no change over V2.

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:

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: 42.0
slices:
- sources:
  - layer_range: [0, 32]
    model: akjindal53244/Llama-3.1-Storm-8B
    parameters:
      density: 0.8
      weight: 0.25
  - layer_range: [0, 32]
    model: arcee-ai/Llama-3.1-SuperNova-Lite
    parameters:
      density: 0.8
      weight: 0.33
  - layer_range: [0, 32]
    model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
    parameters:
      density: 0.8
      weight: 0.42
  - layer_range: [0, 32]
    model: unsloth/Meta-Llama-3.1-8B-Instruct
tokenizer_source: union

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	30.19
IFEval (0-Shot)	77.07
BBH (3-Shot)	32.70
MATH Lvl 5 (4-Shot)	20.09
GPQA (0-shot)	9.96
MuSR (0-shot)	9.09
MMLU-PRO (5-shot)	32.26