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metadata
language:
  - en

kudos to that one dude on /lmg/ for shouting out this model because I dig it. this is my first time uploading something so if something on HF is broken I simply do not care


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

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:

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