Downloads · 30 days
864
13% of all-time downloads
QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF
Gemma-2-Ataraxy-v2-9B-GGUF is a machine learning model from QuantFactory. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
Downloads · 30 days
864
13% of all-time downloads
All-time downloads
6.7K
Public
Repo size
84.7 GB
Likes
2
Public
Click a slice to open those files.
.gguf84.7 GB · 100%
From the Hugging Face model README
This is quantized version of lemon07r/Gemma-2-Ataraxy-v2-9B created using llama.cpp
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 but using better models this time.

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.
Use Gemma 2 format.
This model was merged using the SLERP merge method.
This is a merge of pre-trained language models created using mergekit.
The following models were included in the merge:
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
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.