--- base_model: - mistralai/Mixtral-8x7B-v0.1 - mistralai/Mixtral-8x7B-Instruct-v0.1 - jondurbin/bagel-dpo-8x7b-v0.2 - cognitivecomputations/dolphin-2.7-mixtral-8x7b - NeverSleep/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss - ycros/BagelMIsteryTour-v2-8x7B - smelborp/MixtralOrochi8x7B library_name: transformers tags: - mergekit - merge --- yum yum GGUF quants in my tum :^) enjoy lmg and vali, original model card below I got banned for chatting with femanon, but if anyone has requests you can reach out via the ST Discord
# maid-yuzu-v8-alter This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). v7's approach worked better than I thought, so I tried something even weirder as a test. I don't think a proper model will come out, but I'm curious about the results. ## Merge Details ### Merge Method This model was merged using the SLERP merge method. This models were merged using the SLERP method in the following order: maid-yuzu-v8-base: mistralai/Mixtral-8x7B-v0.1 + mistralai/Mixtral-8x7B-Instruct-v0.1 = 0.5 maid-yuzu-v8-step1: above + jondurbin/bagel-dpo-8x7b-v0.2 = 0.25 maid-yuzu-v8-step2: above + cognitivecomputations/dolphin-2.7-mixtral-8x7b = 0.25 maid-yuzu-v8-step3: above + NeverSleep/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss = 0.25 maid-yuzu-v8-step4-alter: above + ycros/BagelMIsteryTour-v2-8x7B = 0.5 maid-yuzu-v8-alter: above + smelborp/MixtralOrochi8x7B = 0.5 ### Models Merged The following models were included in the merge: * [smelborp/MixtralOrochi8x7B](https://huggingface.co/smelborp/MixtralOrochi8x7B) * ../maid-yuzu-v8-step4-alter ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: model: path: ../maid-yuzu-v8-step4-alter dtype: bfloat16 merge_method: slerp parameters: t: - value: 0.5 slices: - sources: - layer_range: [0, 32] model: model: path: ../maid-yuzu-v8-step4-alter - layer_range: [0, 32] model: model: path: smelborp/MixtralOrochi8x7B ```