only about 8000 training observations but the baseline model used the same data.
I use ViT(visual transformer) for extracting a semantic representation. it comes with its own feature extractor that normalizes and rescales the images
yes:
bi_encoder.eval()
for batch in loader:
\twith torch.no_grad():
\t\tproba = bi_encoder(batch)
…