ShadowPEFT brings detachable shadow models to Hugging Face's PEFT library
The Hong Kong research team put its stateful adapter into PEFT's main branch, trading LoRA-style merging for a parallel network.
By RuntimeWire Staff · Published
Primary source: Hugging Face Newsroom
Why it matters
Native support in PEFT puts ShadowPEFT in developers' existing fine-tuning workflow, giving a research team distribution while exposing the method to broader testing.
Researchers Xianming Li, Zongxi Li and Tsz-fung Andrew Lee have brought ShadowPEFT into the main branch of Hugging Face's PEFT library, giving developers a new way to fine-tune a large model through a smaller trainable model that can later run on its own.…
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