This article details a method for training large language models (LLMs) for code generation using a secure, local WebAssembly-based code interpreter and reinforcement learning with Group Relative Policy Optimization (GRPO). It covers the setup, training process, evaluation, and potential next steps.
This tutorial guides readers on how to fine-tune the Mistral 7B large language model using QLoRA with the Axolotl library, focusing on managing limited GPU resources for efficient training. It covers environment setup, dataset creation, configuration of QLoRA hyperparameters, the fine-tuning process, and testing the fine-tuned model.
