The Smol Training Playbook on Hugging Face provides a comprehensive guide for efficiently training machine learning models using the Hugging Face ecosystem. It emphasizes best practices and methodologies for optimizing training processes, making it accessible for both beginners and experienced practitioners. The playbook also includes practical examples and resources to enhance the learning experience.

CollabLLM is a framework that enables training of collaborative language models to enhance multi-turn conversations by computing multiturn-aware rewards. Users can easily set up their environment, generate synthetic data, and customize metrics and datasets for specific tasks. The project aims to shift language models from passive responders to active collaborators in interactive settings.