Philipp Schmid • 4/22/2024

Efficiently fine-tune Llama 3 with PyTorch FSDP and Q-Lora

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This article provides a step-by-step tutorial for efficiently fine-tuning large language models like Meta's Llama 3 70B. It explains how to use PyTorch FSDP (Fully Sharded Data Parallel) and Q-Lora, combined with Hugging Face's TRL and PEFT libraries, to reduce memory requirements and enable training on consumer-grade GPUs. The guide covers environment setup, dataset preparation, and the fine-tuning process.

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#large language models #Llama 3 #Fine Tuning
Efficiently fine-tune Llama 3 with PyTorch FSDP and Q-Lora

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