--- library_name: transformers tags: - mergekit - merge base_model: - nbeerbower/Gemma2-Gutenberg-Doppel-9B - ifable/gemma-2-Ifable-9B - unsloth/gemma-2-9b-it - wzhouad/gemma-2-9b-it-WPO-HB model-index: - name: Gemma-2-Ataraxy-v3i-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: 42.03 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 38.24 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 0.15 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 10.4 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 1.76 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 35.18 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-9B name: Open LLM Leaderboard --- [![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory) # QuantFactory/Gemma-2-Ataraxy-v3i-9B-GGUF This is quantized version of [lemon07r/Gemma-2-Ataraxy-v3i-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v3i-9B) created using llama.cpp # Original Model Card # Gemma-2-Ataraxy-v3i-9B Another experimental model. This one is in the vein of advanced 2.1, but we replace the simpo model used in the original recipe, with a different simpo model, that was more finetuned with writing in mind, ifable. We also use another writing model, which was trained on gutenberg. We use this one at a higher density because SPPO, on paper is the superior training method, to simpo, and quite frankly, ifable is finicky to work with, and can end up being a little too strong.. or heavy in merges. It's a very strong writer but it introduced quite a bit slop in v2. This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## GGUF https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v3i-9B-Q8_0-GGUF ## Merge Details ### Merge Method This model was merged using the della merge method using [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-it) as a base. ### Models Merged The following models were included in the merge: * [nbeerbower/Gemma2-Gutenberg-Doppel-9B](https://huggingface.co/nbeerbower/Gemma2-Gutenberg-Doppel-9B) * [ifable/gemma-2-Ifable-9B](https://huggingface.co/ifable/gemma-2-Ifable-9B) * [wzhouad/gemma-2-9b-it-WPO-HB](https://huggingface.co/wzhouad/gemma-2-9b-it-WPO-HB) ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: unsloth/gemma-2-9b-it dtype: bfloat16 merge_method: della parameters: epsilon: 0.1 int8_mask: 1.0 lambda: 1.0 normalize: 1.0 slices: - sources: - layer_range: [0, 42] model: unsloth/gemma-2-9b-it - layer_range: [0, 42] model: wzhouad/gemma-2-9b-it-WPO-HB parameters: density: 0.55 weight: 0.6 - layer_range: [0, 42] model: nbeerbower/Gemma2-Gutenberg-Doppel-9B parameters: density: 0.35 weight: 0.6 - layer_range: [0, 42] model: ifable/gemma-2-Ifable-9B parameters: density: 0.25 weight: 0.4 ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_lemon07r__Gemma-2-Ataraxy-v3i-9B) | Metric |Value| |-------------------|----:| |Avg. |21.29| |IFEval (0-Shot) |42.03| |BBH (3-Shot) |38.24| |MATH Lvl 5 (4-Shot)| 0.15| |GPQA (0-shot) |10.40| |MuSR (0-shot) | 1.76| |MMLU-PRO (5-shot) |35.18|