maid-yuzu-v4
This is a merge of pre-trained language models created using mergekit.
This model is a model that I merged with several models I know because I had leftover credits for merging. Of course, the results are not good. Please do not use it.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using mistralai/Mixtral-8x7B-v0.1 as a base.
Models Merged
The following models were included in the merge:
- cognitivecomputations/dolphin-2.7-mixtral-8x7b
- Sao10K/Sensualize-Mixtral-bf16
- jondurbin/bagel-dpo-8x7b-v0.2
- mistralai/Mixtral-8x7B-v0.1 + Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
- smelborp/MixtralOrochi8x7B
Configuration
The following YAML configuration was used to produce this model:
base_model:
model:
path: mistralai/Mixtral-8x7B-v0.1
dtype: bfloat16
merge_method: dare_ties
slices:
- sources:
- layer_range: [0, 32]
model:
model:
path: smelborp/MixtralOrochi8x7B
parameters:
density: 0.75
weight: 0.7
- layer_range: [0, 32]
model:
model:
path: cognitivecomputations/dolphin-2.7-mixtral-8x7b
parameters:
density: 0.6
weight: 0.1
- layer_range: [0, 32]
model:
model:
path: jondurbin/bagel-dpo-8x7b-v0.2
parameters:
density: 0.6
weight: 0.1
- layer_range: [0, 32]
model:
lora:
path: Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
model:
path: mistralai/Mixtral-8x7B-v0.1
parameters:
density: 0.5
weight: 0.25
- layer_range: [0, 32]
model:
model:
path: Sao10K/Sensualize-Mixtral-bf16
parameters:
density: 0.5
weight: 0.2
- layer_range: [0, 32]
model:
model:
path: mistralai/Mixtral-8x7B-v0.1
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