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RichardErkhov/
lemon07r_-_Gemma-2-Ataraxy-v2-9B-gguf

Name: lemon07r_-_Gemma-2-Ataraxy-v2-9B-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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Gemma-2-Ataraxy-v2-9B - GGUF

Model creator: https://huggingface.co/lemon07r/
Original model: https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v2-9B/

Name	Quant method	Size
Gemma-2-Ataraxy-v2-9B.Q2_K.gguf	Q2_K	3.54GB
Gemma-2-Ataraxy-v2-9B.IQ3_XS.gguf	IQ3_XS	3.86GB
Gemma-2-Ataraxy-v2-9B.IQ3_S.gguf	IQ3_S	4.04GB
Gemma-2-Ataraxy-v2-9B.Q3_K_S.gguf	Q3_K_S	4.04GB
Gemma-2-Ataraxy-v2-9B.IQ3_M.gguf	IQ3_M	4.19GB
Gemma-2-Ataraxy-v2-9B.Q3_K.gguf	Q3_K	4.43GB
Gemma-2-Ataraxy-v2-9B.Q3_K_M.gguf	Q3_K_M	4.43GB
Gemma-2-Ataraxy-v2-9B.Q3_K_L.gguf	Q3_K_L	4.78GB
Gemma-2-Ataraxy-v2-9B.IQ4_XS.gguf	IQ4_XS	4.86GB
Gemma-2-Ataraxy-v2-9B.Q4_0.gguf	Q4_0	5.07GB
Gemma-2-Ataraxy-v2-9B.IQ4_NL.gguf	IQ4_NL	5.1GB
Gemma-2-Ataraxy-v2-9B.Q4_K_S.gguf	Q4_K_S	5.1GB
Gemma-2-Ataraxy-v2-9B.Q4_K.gguf	Q4_K	5.37GB
Gemma-2-Ataraxy-v2-9B.Q4_K_M.gguf	Q4_K_M	5.37GB
Gemma-2-Ataraxy-v2-9B.Q4_1.gguf	Q4_1	5.55GB
Gemma-2-Ataraxy-v2-9B.Q5_0.gguf	Q5_0	6.04GB
Gemma-2-Ataraxy-v2-9B.Q5_K_S.gguf	Q5_K_S	6.04GB
Gemma-2-Ataraxy-v2-9B.Q5_K.gguf	Q5_K	6.19GB
Gemma-2-Ataraxy-v2-9B.Q5_K_M.gguf	Q5_K_M	6.19GB
Gemma-2-Ataraxy-v2-9B.Q5_1.gguf	Q5_1	6.52GB
Gemma-2-Ataraxy-v2-9B.Q6_K.gguf	Q6_K	7.07GB
Gemma-2-Ataraxy-v2-9B.Q8_0.gguf	Q8_0	9.15GB

Original model description:

library_name: transformers tags:

mergekit
merge base_model:
ifable/gemma-2-Ifable-9B
jsgreenawalt/gemma-2-9B-it-advanced-v2.1 model-index:
name: Gemma-2-Ataraxy-v2-9B 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: 21.36 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B 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: 39.8 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B 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: 0.83 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B 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: 12.3 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B 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: 4.88 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B 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: 35.79 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B name: Open LLM Leaderboard

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.

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:

yaml

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.

RichardErkhov/lemon07r_-_Gemma-2-Ataraxy-v2-9B-gguf