You can also manually replicate the results of the pipeline if you'd like.

def run_inference(model, video):
     # (num_frames, num_channels, height, width)
     perumuted_sample_test_video = video.permute(1, 0, 2, 3)
     inputs = {
         "pixel_values": perumuted_sample_test_video.unsqueeze(0),
         "labels": torch.tensor(
             [sample_test_video["label"]]
         ),  # this can be skipped if you don't have labels available.
     }