You just move the model to the device. Check out the new distributed inference tutorial, and install accelerate from dev to make use of the new API if you want to do split_by_processes. Otherwise pass your dataloader to Accelerator.prepare and do model.to(state.device):
Using the DDP wrapper on your model is only relevant when you want to update the gradients (that’s what it’s designed there for), so inference just load the model on the device normally