runtime error

Space not ready. Reason: Error, exitCode: 1, message: None

Container logs:

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Working with z of shape (1, 256, 16, 16) = 65536 dimensions.
Downloading: "https://download.pytorch.org/models/vgg16-397923af.pth" to /home/user/.cache/torch/hub/checkpoints/vgg16-397923af.pth

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Downloading vgg_lpips model from https://heibox.uni-heidelberg.de/f/607503859c864bc1b30b/?dl=1 to taming/modules/autoencoder/lpips/vgg.pth

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loaded pretrained LPIPS loss from taming/modules/autoencoder/lpips/vgg.pth
VQLPIPSWithDiscriminator running with hinge loss.
Loaded VQGAN from /home/user/.cache/dalle/vqgan.1024.model.ckpt and /home/user/.cache/dalle/vqgan.1024.config.yml
Traceback (most recent call last):
  File "app.py", line 40, in <module>
    load_obj = torch.load(model_path)
  File "/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", line 712, in load
    return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
  File "/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", line 1046, in _load
    result = unpickler.load()
  File "/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", line 1016, in persistent_load
    load_tensor(dtype, nbytes, key, _maybe_decode_ascii(location))
  File "/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", line 1001, in load_tensor
    wrap_storage=restore_location(storage, location),
  File "/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", line 176, in default_restore_location
    result = fn(storage, location)
  File "/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", line 152, in _cuda_deserialize
    device = validate_cuda_device(location)
  File "/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", line 136, in validate_cuda_device
    raise RuntimeError('Attempting to deserialize object on a CUDA '
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.