Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
Paper
•
2203.05482
•
Published
•
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:
merge_method: linear
models:
- model: snek+jeiku/Theory_of_Mind_128_StableLM
parameters:
weight: 1
- model: snek+jeiku/Everything_v3_128_StableLM
parameters:
weight: 1
- model: snek+jeiku/Gnosis_StableLM
parameters:
weight: 1
- model: snek+jeiku/Toxic_DPO_StableLM
parameters:
weight: 1
- model: snek+jeiku/No_Robots_Alpaca_StableLM
parameters:
weight: 1
- model: snek+jeiku/Theory_of_Mind_RP_128_StableLM
parameters:
weight: 1
- model: snek+jeiku/Bluemoon_cleaned_StableLM
parameters:
weight: 1
- model: snek+jeiku/RPGPT_StableLM
parameters:
weight: 1
- model: snek+jeiku/LimaRP_StableLM
parameters:
weight: 1
- model: snek+jeiku/PIPPA_128_StableLM
parameters:
weight: 1
dtype: float16