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--- |
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base_model: lemon07r/Gemma-2-Ataraxy-v2-9B |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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- llama-cpp |
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- gguf-my-repo |
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model-index: |
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- name: Gemma-2-Ataraxy-v2-9B |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 21.36 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 39.8 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 0.83 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 12.3 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 4.88 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 35.79 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2-9B |
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name: Open LLM Leaderboard |
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--- |
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# Triangle104/Gemma-2-Ataraxy-v2-9B-Q8_0-GGUF |
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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. |
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Refer to the [original model card](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v2-9B) for more details on the model. |
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--- |
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Model details: |
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- |
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Gemma 2 Ataraxy v2 9B |
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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. |
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Ataraxy GGUF / EXL2 Quants |
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Bartowski quants (imatrix): https://huggingface.co/bartowski/Gemma-2-Ataraxy-v2-9B-GGUF |
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Mradermacher quants (static): https://huggingface.co/mradermacher/Gemma-2-Ataraxy-v2-9B-GGUF |
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Mradermacher quants (imatrix): https://huggingface.co/mradermacher/Gemma-2-Ataraxy-v2-9B-i1-GGUF |
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Bartowski and mradermacher use different calibration data for their imatrix quants I believe, and the static quant of course uses none. Pick your poison. |
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More coming soon. Format |
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Use Gemma 2 format. Merge Details Merge Method |
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This model was merged using the SLERP merge method. Models Merged |
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This is a merge of pre-trained language models created using mergekit. |
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The following models were included in the merge: |
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ifable/gemma-2-Ifable-9B |
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jsgreenawalt/gemma-2-9B-it-advanced-v2.1 |
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Configuration |
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The following YAML configuration was used to produce this model: |
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base_model: ifable/gemma-2-Ifable-9B dtype: bfloat16 merge_method: slerp parameters: t: |
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filter: self_attn value: [0.0, 0.5, 0.3, 0.7, 1.0] |
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filter: mlp value: [1.0, 0.5, 0.7, 0.3, 0.0] |
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value: 0.5 slices: |
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sources: |
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layer_range: [0, 42] model: jsgreenawalt/gemma-2-9B-it-advanced-v2.1 |
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layer_range: [0, 42] model: ifable/gemma-2-Ifable-9B |
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Open LLM Leaderboard Evaluation Results |
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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 |
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Second highest ranked open weight model in EQ-Bench. |
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--- |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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llama-cli --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q8_0-GGUF --hf-file gemma-2-ataraxy-v2-9b-q8_0.gguf -p "The meaning to life and the universe is" |
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``` |
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### Server: |
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```bash |
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llama-server --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q8_0-GGUF --hf-file gemma-2-ataraxy-v2-9b-q8_0.gguf -c 2048 |
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``` |
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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. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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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). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q8_0-GGUF --hf-file gemma-2-ataraxy-v2-9b-q8_0.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo Triangle104/Gemma-2-Ataraxy-v2-9B-Q8_0-GGUF --hf-file gemma-2-ataraxy-v2-9b-q8_0.gguf -c 2048 |
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``` |
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