
Hugging Face has released the 'Ultra-Scale Playbook', a free and open-source guide designed for training large language models (LLMs) on GPU clusters. The playbook, which spans 150 pages, covers a range of topics including 5D parallelism, ZeRO, and fast CUDA kernels, aimed at optimizing the training process across varying scales from single GPU setups to thousands. It is based on insights from over 4,000 scaling experiments and includes real-world case studies to illustrate effective training techniques. The playbook is intended to assist researchers and practitioners in overcoming scaling bottlenecks and improving efficiency in AI model training.







The Hugging Face Ultra-Scale Playbook provides a comprehensive guide to scaling AI models to large compute resources. It covers strategies for efficiently using GPUs and TPUs, optimizations for memory and compute performance, and best practices for distributed training. The… https://t.co/oE5PORgHi1 https://t.co/7IvMWQ5VNF
Amazing. Notebook LM explaining the ultra scale playbook. A very important topic today because the GPU poor of today will be building the AI of tomorrow, hopefully. At least my hope is so. https://t.co/Xsmts3f06w
I’m really looking forward to this. Playbook on distributed LLM training from the @huggingface team. Will share my learnings as I read. https://t.co/bHPhzkPZ9a