Fine-tuning Gemma 3 270M Locally

Google's Gemma 3 270M model can be fine-tuned locally using just 0.5 GB RAM. The tutorial demonstrates using Unsloth and HuggingFace transformers to fine-tune the model for chess move prediction. The process involves loading the model, configuring LoRA for efficient training, preparing a chess dataset, and training with Show more