metadata

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

maid-yuzu-v8-alter

This is a merge of pre-trained language models created using 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
../maid-yuzu-v8-step4-alter

Configuration

The following YAML configuration was used to produce this model:

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