Philipp Schmid • 4/13/2023

Train and Deploy BLOOM with Amazon SageMaker and PEFT

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This tutorial demonstrates how to apply Parameter Efficient Fine-Tuning (PEFT) methods, specifically LoRA, to fine-tune the 7B parameter BLOOMZ model on a single GPU. It covers setting up the environment with Hugging Face libraries, preparing a dataset, performing efficient fine-tuning with 8-bit quantization, and deploying the trained model to an Amazon SageMaker endpoint for inference.

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#Lora #Model Deployment #Amazon Sagemaker
Train and Deploy BLOOM with Amazon SageMaker and PEFT

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