GitLab

Text encoders can now return other values to the CONDITIONING than the cond
and pooled output.

Made token instance check more flexible so it also works with integers from numpy arrays or long tensors

Fix issue with not loading the SSD1B clip correctly.

Use fp16 text encoder weights for CPU inference to lower memory usage.

Use a simple CLIP model implementation instead of the one from
transformers.

This will allow some interesting things that would too hackish to implement
using the transformers implementation.

More generic clip model class that can be used on more types of text
encoders.

Don't apply weighting algorithm when weight is 1.0

Don't compute an empty token output when it's not needed.

Do inference in fp32 to make sure quality stays the exact same.