The Definitive Fine-Tuning Guide for 3D Generation Models

Fine-tuning the TRELLIS.2 3D generation model can improve its performance on specific tasks, such as generating more accurate shoe soles. This process uses Low-Rank Adaptation (LoRA) to efficiently adapt only the necessary components of the model's pipeline, like the sparse-structure flow DiT. The guide provides practical instructions and scripts for running the training process on Hugging Face Jobs or locally using Docker. It also details the five main stages of the TRELLIS.2 architecture, from image encoding with DINOv3 to final mesh creation. This approach allows for targeted improvements without retraining the entire large model.