Releases: explosion/spacy-curated-transformers
v2.1.2: Avoid specifying spacy as an install dependency
Specifying spaCy as a dependency causes the models to depend on spaCy as well, which causes the model artifacts to be pinned to a particular range of spaCy versions. spaCy's download already specifies which models it's compatible with, so we don't want this --- it causes spurious model repackaging and redownloading for irrelevant changes.
v0.3.0: Avoid depending on spaCy itself
Drop the direct dependency on spaCy, to avoid requirement circles.
Specifically, we're changing models to no longer specify a spaCy version as a requirement, to allow models to be forward compatible. However, the transformer models depend on this library. If it then pulls in spaCy, we end up with spaCy in the requirements again.
Relax Thinc pin to allow numpy v2
Thinc 9.0.0 is built against numpy v1, while Thinc 9.1.0 is built against numpy v2. Relax the thinc pin to allow compatibility with more recent numpy.
v2.0.0: use Curated Transformers 2.0 and discriminative learning rate schedule
v0.2.2: Make `DocTransformerOutput` serializable with msgpack
✨ New features and improvements
- Make
DocTransformerOutput
serializable with msgpack (#29).
v0.2.1: Add 'init fill-curated-transformer' CLI
✨ New features and improvements
- Add
init fill-curated-transformer
CLI command (#16, #22).
🔴 Bug fixes
v0.2.0: Support for replacing listeners
Fix handling of empty docs
Split out spaCy entry points from curated-transformers
This new package contains the entry points and spaCy/Thinc wrapping for curated-transformers
that originally resided in the curated-transformers
package.