Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
Paper
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2311.03099
•
Published
•
30
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.
This model was merged using the DARE TIES merge method using mistralai/Mixtral-8x7B-v0.1 as a base.
The following models were included in the merge:
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