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
withstrict=False
, due to incompatibilities related tostate_dict
keys betweentransformers
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.