I cannot reproduce the issue, as the torch.hub.load method would already load the model as described in the docs:
>>> import torch
>>> waveglow = torch.hub.load('NVIDIA/DeepLearningExamples:torchhub', 'nvidia_waveglow', model_math='fp32')
Downloading: "https://github.com/NVIDIA/DeepLearningExamples/archive/torchhub.zip" to /root/.cache/torch/hub/torchhub.zip
Downloading checkpoint from https://api.ngc.nvidia.com/v2/models/nvidia/waveglow_ckpt_fp32/versions/19.09.0/files/nvidia_waveglowpyt_fp32_20190427
>>> waveglow
WaveGlow(
  (upsample): ConvTranspose1d(80, 80, kernel_size=(1024,), stride=(256,))
  (WN): ModuleList(
    (0): WN(
      (in_layers): ModuleList(
        (0): Conv1d(512, 1024, kernel_size=(3,), stride=(1,), padding=(1,))
        (1): Conv1d(512, 1024, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,))
   [...]

Calling torch.load afterwards on it yields the expected seek error:
>>> torch.load(waveglow, map_location='cpu')

AttributeError: 'WaveGlow' object has no attribute 'seek'

PS: you can post code snippets by wrapping them into three backticks ```, which makes debugging easier and allows to index the code for a better search.