v1.4.0: Update transformers pin

release-v1.4.0

Upd config

v1.3.9: Publish more wheels

Publish wheels for Python 3.13 and Linux ARM.

v1.3.8: Fix wheels on v1.3.7 release

v1.3.7 updates the transformers pin to allow use of new models such as ModernBERT. However there was an error in the wheel publication. This release corrects it.

v1.3.6

✨ New features and improvements

• Bump transforms pin to allow up to 4.41.x
• Updates to the test suite

👥 Contributors

@danieldk, @honnibal, @ines, @svlandeg

v1.3.5

• Relax spaCy constraint to <4.1.0 to support spaCy 4.
• Fix a compilation issue with recent Cython 3 versions (#415).

v1.3.4

• Extend support for transformers to v4.36.

v1.3.3

• Drop support for Python 3.6.
• Extend support for transformers to v4.35.

v1.3.2

• Extend support for transformers to v4.34.

v1.3.1

This release addresses incompatibilities related to saving and loading models across a range of transformers versions following changes in transformers v4.31.

• Extend support to transformers v4.33 (#402).
• Add fallback to load state_dict with strict=False, due to incompatibilities related to state_dict keys between transformers v4.30 and v4.31 (#398).

Options for improved pipeline package compatibility

If you are packaging models with spacy package and you'd like to avoid having your users run into the fallback strict=False loading and warnings related to state_dict keys, you may want to add a stricter transformers requirement that corresponds to the version used during training.

If you're training with the newest supported transformers version (v4.33.x), you could currently add transformers>=4.31 to your package requirements. Note that this would restrict your users to Python 3.8+ and PyTorch 1.9+ due to transformers requirements.

Create meta.json with your additional requirements:

{
  "requirements": ["transformers>=4.31"]
}

Package with spacy package:

spacy package --meta meta.json input_dir output_dir

The requirement transformers>=4.31 will be added to any other package requirements that are automatically determined based on your pipeline config.

v1.3.0

NOTE: This release has been yanked on PyPI because of the incompatibilities between saved pipelines for transformers v4.30 and v4.31. Please use spacy-transformers v1.2.x instead.

• Update build constraints to use numpy v1.25+ for python 3.9+ (#394).

• Extend support for transformers up to v4.31 (#395).

  ⚠️ After upgrading to transformers v4.31+ you may not be able to load certain older saved pipelines. All older saved models can still be loaded with transformers<4.31 or you can retrain your models so they are compatible with newer versions of transformers (#395).

  If you have created packages with spacy package using spacy-transformers v1.2 or earlier, those package requirements should be restricted to compatible versions of transformers and should not require updates.