Gemma-2-Ataraxy-Remix-9B-Q8_0-GGUF

This is the Q8_0 GGUF for people to try while I evaluate my merges.

Another test model. Ignore this for now. Probably wont be good but I am testing a lot of stuff.

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

Merge Details

Merge Method

This model was merged using the Model Stock merge method using unsloth/gemma-2-9b-it 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/gemma-2-9b-it
dtype: bfloat16
merge_method: model_stock
slices:
- sources:
  - layer_range: [0, 42]
    model: lemon07r/Gemma-2-Ataraxy-9B
  - layer_range: [0, 42]
    model: lemon07r/Gemma-2-Ataraxy-v2-9B
  - layer_range: [0, 42]
    model: lemon07r/Gemma-2-Ataraxy-v2a-9B
  - layer_range: [0, 42]
    model: jsgreenawalt/gemma-2-9B-it-advanced-v2.1
  - layer_range: [0, 42]
    model: ifable/gemma-2-Ifable-9B
  - layer_range: [0, 42]
    model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
  - layer_range: [0, 42]
    model: princeton-nlp/gemma-2-9b-it-SimPO
  - layer_range: [0, 42]
    model: wzhouad/gemma-2-9b-it-WPO-HB
  - layer_range: [0, 42]
    model: nbeerbower/gemma2-gutenberg-9B
  - layer_range: [0, 42]
    model: grimjim/Gemma2-Nephilim-v3-9B
  - layer_range: [0, 42]
    model: recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
  - layer_range: [0, 42]
    model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
  - layer_range: [0, 42]
    model: unsloth/gemma-2-9b-it

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	29.21
IFEval (0-Shot)	70.83
BBH (3-Shot)	41.59
MATH Lvl 5 (4-Shot)	1.28
GPQA (0-shot)	11.86
MuSR (0-shot)	13.72
MMLU-PRO (5-shot)	35.99

lemon07r
/

Gemma-2-Ataraxy-Remix-9B-Q8_0-GGUF