2min chapter

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February 11th, 2024 | Finding a new software developer job

Hacker News Recap

CHAPTER

Fine Tuning Language Models with RLHF and DPO

This chapter explores the RLHF approach for fine tuning language models using reinforcement learning and human feedback. It discusses the process of training a model using the Data Dreamer library and emphasizes the alignment of model outputs to human preferences through the DPO dataset. The chapter also touches on abstraction levels in ML libraries, the importance of documentation, and the need for diverse examples.

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