Fine-tuning Llama 2 for Tone or Style Using Shakespeare Dataset
Learn how to fine-tune the Llama 2 language model for tone or style using a custom dataset in this 18-minute video tutorial. Explore the process of adapting the model to mimic Shakespearean language as an example. Discover techniques for loading Llama 2 with bitsandbytes, implementing LoRA for efficient fine-tuning, and selecting appropriate target modules. Gain insights into setting optimal training parameters, including batch size, gradient accumulation, and warm-up settings. Master the use of AdamW optimizer and learn to evaluate training loss effectively. Troubleshoot common issues in Google Colab and run inference with your newly fine-tuned model. Access additional resources for embedding creation, supervised fine-tuning, and advanced scripts to enhance your language model customization skills.