Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
Paper
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2203.05482
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Published
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7
This is a merge of pre-trained language models created using mergekit.
This model was merged using the Linear merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
dtype: float16
merge_method: linear
modules:
default:
slices:
- sources:
- layer_range: [0, 32]
model: mistralai/Mistral-7B-Instruct-v0.2
parameters:
density: 0.5
weight: 0.5
- layer_range: [0, 32]
model: BioMistral/BioMistral-7B
parameters:
density: 0.5
weight: 0.5
- layer_range: [0, 32]
model: OdiaGenAI/mistral_hindi_7b_base_v1
parameters:
density: 0.5
weight: 0.5
- layer_range: [0, 32]
model: mistralai/Mistral-7B-v0.1
parameters:
density: 0.5
weight: 0.5