Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:# Run inference directly in the terminal:
llama cli -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:Use Docker
docker model run hf.co/QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:
QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF
This is quantized version of lemon07r/Gemma-2-Ataraxy-v2-9B created using llama.cpp
Original Model Card
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 but using better models this time.
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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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard21.360
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard39.800
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.830
- acc_norm on GPQA (0-shot)Open LLM Leaderboard12.300
- acc_norm on MuSR (0-shot)Open LLM Leaderboard4.880
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard35.790
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF:# Run inference directly in the terminal: llama cli -hf QuantFactory/Gemma-2-Ataraxy-v2-9B-GGUF: