Half the data was geared towards better reasoning (EvolKit-20k and reasoning-base-20k), the other half will help to de-censor the model (WizardLM data set).

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:

Configuration

The following YAML configuration was used to produce this model:

yaml

slices:
  - sources:
      - model: theprint/ReWiz-7B
        layer_range: [0, 32]
      - model: theprint/WorldBuilder-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: theprint/ReWiz-7B
parameters:
  t:
    - filter: self_attn
      value: [0.1, 0.5, 0.3, 0.7, 0.9]
    - filter: mlp
      value: [0.9, 0.5, 0.7, 0.3, 0.1]
    - value: 0.5
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	15.66
IFEval (0-Shot)	25.10
BBH (3-Shot)	25.08
MATH Lvl 5 (4-Shot)	2.95
GPQA (0-shot)	2.57
MuSR (0-shot)	16.39
MMLU-PRO (5-shot)	21.90

theprint/ReWiz-Worldbuilder-7B