Post-training methods for language models

This blog post provides a comprehensive overview of post-training methods for language models, detailing techniques like supervised fine-tuning, continual learning, and reinforcement learning. It explores how these methods transform large language models from generalist to specialized tools for practical applications. Additionally, it introduces the open source Training Hub library, which offers a unified platform for developers to experiment with these advanced post-training techniques.