Fine-tune LLaMa 2 in Google Colab
In this video, we fine-tune the Llama 2 language model using QLoRA and bitsandbytes techniques on a T4 GPU. The notebook loads the dataset, sets training parameters, trains the model, saves the trained model, and generates text using the trained model. It also reloads the model in FP16 and merges it with LoRA weights. The notebook includes code to push the model to the Hugging Face hub.
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This tutorial is based on Jupyter notebook: https://github.com/mlabonne/llm-cours...