Releases: explosion/spacy-transformers
Releases · explosion/spacy-transformers
Release list
v1.1.5
✨ New features and improvements
- Extend support for
transformersup to v4.17.x.
👥 Contributors
v1.1.4
✨ New features and improvements
- Extend support for
transformersup to v4.15.x.
👥 Contributors
v1.1.3
✨ New features and improvements
- Extend support for
transformersup to v4.12.x.
👥 Contributors
v1.1.2
v1.1.1
v1.1.0
✨ New features and improvements
- Refactor and improve transformer serialization for better support of inline transformer components and replacing listeners.
- Provide the transformer model output as
ModelOutputinstead of tuples inTransformerData.model_outputandFullTransformerBatch.model_output. For backwards compatibility, the tuple format remains available underTransformerData.tensorsandFullTransformerBatch.tensors. See more details in the transformer API docs. - Add support for
transformer_configsettings such asoutput_attentions. Additional output is stored underTransformerData.model_output. More details in theTransformerModeldocs. - Add support for mixed-precision training.
- Improve training speed by streamlining allocations for tokenizer output.
- Extend support for
transformersup to v4.11.x.
🔴 Bug fixes
- Fix support for GPT2 models.
⚠️ Backwards incompatibilities
- The serialization format for
transformercomponents has changed in v1.1 and is not compatible withspacy-transformersv1.0.x. Pipelines trained with v1.0.x can be loaded with v1.1.x, but pipelines saved with v1.1.x cannot be loaded with v1.0.x. TransformerData.tensorsandFullTransformerBatch.tensorsreturn a tuple instead of a list.
👥 Contributors
@adrianeboyd, @bryant1410, @danieldk, @honnibal, @ines, @KennethEnevoldsen, @svlandeg
v1.0.6: Bugfix for replacing listeners
- Fix copying of
grad_factorwhen replacing listeners.
v1.0.5: Bugfix for replacing listeners
- Fix replacing listeners: #277
- Require spaCy 3.1.0 or higher
v1.0.4
- Extend transformers support to
<4.10.0 - Enable pickling of span getters and annotation setters, which is required for multiprocessing with spawn