Vox-cpk.pth.tar _verified_ Jun 2026

: If the checkpoint was saved during training, it likely includes the optimizer's state. This allows training to resume from where it left off, with the same learning rate and parameter updates applied.

: Use PyTorch's torch.load() function to load the checkpoint into your Python environment. vox-cpk.pth.tar

model.load_state_dict(generator_state) model.eval() : If the checkpoint was saved during training,