Papers with on-device customization

1 papers
Crayon: Customized On-Device LLM via Instant Adapter Blending and Edge-Server Hybrid Inference (2024.acl-long)

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Challenge: Large language models are highly advanced to user-requested tasks.
Approach: They propose a device-server hybrid inference strategy for on-device LLM customization . they construct a pool of diverse base adapters and then blend them into a customized adapter .
Outcome: The proposed method can be used on a large scale without extra training . it can be applied to large-scale LLMs without sacrificing the benefits of on-device customization.

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