Philipp Schmid • 1/23/2025

How to align open LLMs in 2025 with DPO and and synthetic data

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This article provides a detailed tutorial on aligning open-source Large Language Models (LLMs) with human preferences using Direct Preference Optimization (DPO). It explains DPO's advantages over traditional RLHF, outlines a method for creating a preference dataset from model outputs, and guides readers through implementing DPO training with the Hugging Face DPOTrainer to improve a fine-tuned model's performance.

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#Post Training #Synthetic Data #Direct Preference Optimization
How to align open LLMs in 2025 with DPO and and synthetic data

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