unsloth-dpo

What problem does it solve?

This Skill streamlines Direct Preference Optimization (DPO) for aligning language models with preference data, significantly reducing memory requirements by allowing the reference model to be set to None.

Core Features & Use Cases

• Memory-Efficient DPO: Train models on preference pairs without needing a separate reference model, ideal for VRAM-constrained environments.
• Alignment: Fine-tune models for specific tones, reasoning styles, or to follow instructions better after an initial Supervised Fine-Tuning (SFT) phase.
• Use Case: You have a base LLM and a dataset of prompts with two responses each (one preferred, one not). Use this Skill to fine-tune the LLM to generate responses more aligned with the preferred style.

Quick Start

Configure and initialize the DPOTrainer using the provided Python script to begin preference optimization.