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
3.0bpw quant of rhplus0831's maid-yuzu-v8-alter, which can be found here: https://huggingface.co/rhplus0831/maid-yuzu-v8-alter. 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