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Gemma 2 Ataraxy v2 9B

Finally, after much testing, a sucessor to the first Gemma 2 Ataraxy 9B. Same kind of recipe, using the same principles, same concept as the last Ataraxy. It's not quite a better overall model, v1 is more well rounded, v2 is a little better at writing but has a little more slop and some other issues. consider this a sidegrade.

Ataraxy

GGUF / EXL2 Quants

Bartowski quants (imatrix): https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-GGUF

Mradermacher quants (static): https://huggingface.co/mradermacher/Gemma-2-Ataraxy-v2-9B-GGUF

Mradermacher quants (imatrix): https://huggingface.co/mradermacher/Gemma-2-Ataraxy-v2-9B-i1-GGUF

Bartowski and mradermacher use different calibration data for their imatrix quants I believe, and the static quant of course uses none. Pick your poison.

More coming soon.

Format

Use Gemma 2 format.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

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

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

base_model: ifable/gemma-2-Ifable-9B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 42]
    model: jsgreenawalt/gemma-2-9B-it-advanced-v2.1
  - layer_range: [0, 42]
    model: ifable/gemma-2-Ifable-9B

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 19.16
IFEval (0-Shot) 21.36
BBH (3-Shot) 39.80
MATH Lvl 5 (4-Shot) 0.83
GPQA (0-shot) 12.30
MuSR (0-shot) 4.88
MMLU-PRO (5-shot) 35.79

Second highest ranked open weight model in EQ-Bench.

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Model size
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Architecture
gemma2

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Inference API
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Evaluation results