base_model: lemon07r/Gemma-2-Ataraxy-v2-9B
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
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
Triangle104/Gemma-2-Ataraxy-v2-9B-Q4_K_M-GGUF
This model was converted to GGUF format from lemon07r/Gemma-2-Ataraxy-v2-9B using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Model details:
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:
ifable/gemma-2-Ifable-9B
jsgreenawalt/gemma-2-9B-it-advanced-v2.1
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.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q4_K_M-GGUF --hf-file gemma-2-ataraxy-v2-9b-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q4_K_M-GGUF --hf-file gemma-2-ataraxy-v2-9b-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q4_K_M-GGUF --hf-file gemma-2-ataraxy-v2-9b-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q4_K_M-GGUF --hf-file gemma-2-ataraxy-v2-9b-q4_k_m.gguf -c 2048