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
slices:
- sources:
- layer_range: [0, 64]
model: /workspace_nas/study/Kaggle/medicalllm/models/QwQ-32B
parameters:
weight: 0.5
- layer_range: [0, 64]
model: /workspace_nas/study/Kaggle/medicalllm/models/Qwen2.5-32B-Instruct-medical_llm_elastic_search_250227
parameters:
weight: 0.5
- layer_range: [0, 64]
model: /workspace_nas/study/Kaggle/medicalllm/models/merge_qwqMqwenPft05
parameters:
weight: 0.5