--- 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-Q5_K_S-GGUF This model was converted to GGUF format from [`lemon07r/Gemma-2-Ataraxy-v2-9B`](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v2-9B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v2-9B) 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) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q5_K_S-GGUF --hf-file gemma-2-ataraxy-v2-9b-q5_k_s.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q5_K_S-GGUF --hf-file gemma-2-ataraxy-v2-9b-q5_k_s.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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-Q5_K_S-GGUF --hf-file gemma-2-ataraxy-v2-9b-q5_k_s.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q5_K_S-GGUF --hf-file gemma-2-ataraxy-v2-9b-q5_k_s.gguf -c 2048 ```