[palunon]

Nah, transfer learning is when you take a trained model, and train it a little more to better fit your (potentially very different) problem domain. Such as training a cat/dog/etc recognition model on MRI scans.

The goal is usually to have the more fundamental parts of your model already working and you thus need way less domain specific data.

Here, you're not training anything, you're running the models (both the CLIP language model and the unet) in feedforward. That's just deploying your model, not transfer learning.