From Research to Production: Fine-Tuning & Aligning LLMs // Philipp Schmid // AI in Production

// Abstract
Discover the essential steps in transitioning LLMs from research to production, with a focus on effective fine-tuning and alignment strategies. This session delves into how to fine-tune & evaluate LLMs with Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF)/Direct Preference Optimization (DPO), and their practical applications for aligning LLMs with production goals.

// Bio
Philipp Schmid is a Technical Lead at Hugging Face with the mission to democratize good machine learning through open source and open science. …

abstract alignment direct preference optimization feedback fine-tuning focus human human feedback llms optimization production reinforcement reinforcement learning research rlhf session sft strategies supervised fine-tuning