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Releases: explosion/spacy-transformers

v1.3.5

25 Apr 12:54
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  • Relax spaCy constraint to <4.1.0 to support spaCy 4.
  • Fix a compilation issue with recent Cython 3 versions (#415).

v1.3.4

19 Dec 07:41
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  • Extend support for transformers to v4.36.

v1.3.3

08 Nov 10:45
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  • Drop support for Python 3.6.
  • Extend support for transformers to v4.35.

v1.3.2

12 Oct 06:00
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  • Extend support for transformers to v4.34.

v1.3.1

26 Sep 07:08
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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

01 Aug 12:10
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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.

v1.2.5

12 Jun 11:30
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  • Extend support for transformers up to v4.30.x.

v1.2.4

22 May 17:47
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  • Extend support for transformers up to v4.29.x.

v1.2.3

17 Apr 13:53
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  • Extend support for transformers up to v4.28.x.
  • Implement coalesced pooling over entire batches (#368).

v1.2.2

18 Feb 07:34
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  • Transformer.predict: do not broadcast to listeners, requires spacy>=3.5.0 (#345)
  • Correct and clarify the handling of empty/zero-length Docs during training and inference (#365)
  • Remove superfluous datatype and device conversions, requires torch>=1.8.0 (#369)
  • Fix memory leak in offsets mapping alignment for fast tokenizers (#373)