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Note Of Unsloth Accelerate Fine-tuning Open Source Project

Introduction

For several months, I have benefited greatly from the Unsloth project, primarily because a significant part of my job involves fine-tuning large language models (LLMs). Fine-tuning LLMs is extremely time-consuming; aside from data collection, the biggest time sink is the endless GPU-powered fine-tuning process.

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[Paper Reading] Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting

Introduction

The accelerated framework is proposed by Huawei Noah's Ark Lab, it replaces the small model used in the original speculative decoding with the shallow sub-network of the large model. Additionally, it employs an extra-trained adapter and the model’s own decoding head to generate speculative tokens, which are then verified by the large model. The subsequent operations are quite similar to the original speculative decoding process.

Read More »[Paper Reading] Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting