v0.5.0

The performances of the contemporary models in this release are improved, most notably for models
not using BERT.

Added

• The scripts/zenodo_upload.py script, a helper for uploading files to a Zenodo deposit.

Changed

• The CharRNN lexer now represent words with last hidden (instead of cell) state of the LSTM and do
  not run on padding anymore.
• Minimal Pytorch version is now 1.9.0
• Minimal Transformers version is now 4.19.0
• Use torch.inference_mode instead of toch.no_grad over all the parser methods.
• BERT lexer batches no longer have an obsolete, always zero word_indices attribute
• DependencyDataset does not have lexicon attributes (ito(lab|tag and their inverse) since we
  don't need these anymore.
• The train_model script now skips incomplete runs with a warning.
• The train_model script has nicer logging, including progress bars to help keep track of the
  experiments.

Fixed

• The first word in the word embeddings lexer vocabulary is not used as padding anymore and has a
  real embedding.
• BERT embeddings are now correctly computed with an attention mask to ignore padding.
• The root token embedding coming from BERT lexers is now an average of non-padding words'
  embeddings
• FastText embeddings are now computed by averaging over non-padding subwords' embeddings.
• In server mode, models are now correctly in eval mode and processing is done
  in torch.inference_mode.

Full Changelog: v0.4.2...v0.5.0