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:

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