For both global and local generation modes, we adopted the 3D pretraining backbone designed for OOMs (as detailed in the previous section) and employed the VP initialization strategy. The generator was trained using the Adam optimizer with a learning rate of 0.0001. The training process lasted for 1,000,000 steps, equivalent to approximately 17 epochs. The batch size was set to 4, and the model consisted of 9 layers. Training was conducted on 4 Tesla-A100-80G GPUs.