This release only include some smaller updates:
- Code was tested with transformers 3.5.1, requirement was updated so that it works with transformers 3.5.1
- As some parts and models require Pytorch >= 1.6.0, requirement was updated to require at least pytorch 1.6.0. Most of the code and models will work with older pytorch versions.
- model.encode() stored the embeddings on the GPU, which required quite a lot of GPU memory when encoding millions of sentences. The embeddings are now moved to CPU once they are computed.
- The CrossEncoder-Class now accepts a max_length parameter to control the truncation of inputs
- The Cross-Encoder predict method has now a apply_softmax parameter, that allows to apply softmax on-top of a multi-class output.