Philipp Schmid • 5/2/2023

How to scale LLM workloads to 20B+ with Amazon SageMaker using Hugging Face and PyTorch FSDP

This article provides a step-by-step guide to scaling large language model (LLM) fine-tuning workloads for models over 20 billion parameters. It details using PyTorch Fully Sharded Data Parallel (FSDP) with the Hugging Face Transformers library on Amazon SageMaker's multi-node, multi-GPU clusters (like p4d.24xlarge instances) to efficiently distribute model training, covering environment setup, data preparation, and the training process.

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#large language models #Hugging Face #Amazon Sagemaker