A fistful of dollars: fine-tune LLaMA 2 7B with QLoRA

Fine-tuning large models doesn't have to be complicated and expensive. In this tutorial, I provide a step-by-step demonstration of the fine-tuning process for a LLaMA 2 7B model. Utilizing a pre-existing script sourced from the TRL library, the configuration is set to leverage the QLoRA algorithm from the Hugging Face PEFT library. The training procedure is executed on a modest AWS GPU instance (g5.xlarge), optimizing cost-effectiveness through the utilization of EC2 Spot Instances, resulting in a total cost of just a few dollars.

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Blog: https://huggingface.co/blog/4bit-tran...
Model + code + training log: https://huggingface.co/juliensimon/ll...
Dataset: https://huggingface.co/datasets/timde...
Amazon EC2 G5 instances: https://aws.amazon.com/ec2/instance-t...

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