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README.md
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---
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base_model:
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- mistralai/Mixtral-8x7B-v0.1
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- mistralai/Mixtral-8x7B-Instruct-v0.1
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- jondurbin/bagel-dpo-8x7b-v0.2
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- cognitivecomputations/dolphin-2.7-mixtral-8x7b
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- NeverSleep/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss
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- ycros/BagelMIsteryTour-v2-8x7B
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- smelborp/MixtralOrochi8x7B
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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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---
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yum yum GGUF quants in my tum :^) enjoy lmg and vali, original model card below
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<hr>
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# maid-yuzu-v8-alter
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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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.
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## Merge Details
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### Merge Method
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This model was merged using the SLERP merge method.
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This models were merged using the SLERP method in the following order:
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maid-yuzu-v8-base: mistralai/Mixtral-8x7B-v0.1 + mistralai/Mixtral-8x7B-Instruct-v0.1 = 0.5
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maid-yuzu-v8-step1: above + jondurbin/bagel-dpo-8x7b-v0.2 = 0.25
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maid-yuzu-v8-step2: above + cognitivecomputations/dolphin-2.7-mixtral-8x7b = 0.25
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maid-yuzu-v8-step3: above + NeverSleep/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss = 0.25
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maid-yuzu-v8-step4-alter: above + ycros/BagelMIsteryTour-v2-8x7B = 0.5
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maid-yuzu-v8-alter: above + smelborp/MixtralOrochi8x7B = 0.5
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### Models Merged
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The following models were included in the merge:
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* [smelborp/MixtralOrochi8x7B](https://huggingface.co/smelborp/MixtralOrochi8x7B)
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* ../maid-yuzu-v8-step4-alter
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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base_model:
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model:
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path: ../maid-yuzu-v8-step4-alter
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dtype: bfloat16
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merge_method: slerp
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parameters:
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t:
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- value: 0.5
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slices:
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- sources:
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- layer_range: [0, 32]
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model:
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model:
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path: ../maid-yuzu-v8-step4-alter
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- layer_range: [0, 32]
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model:
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model:
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path: smelborp/MixtralOrochi8x7B
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```
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