This package comes with an extensive test suite. In order to run the tests,
you’ll usually want to clone the repository and build the package from the
source. This will also install the required development dependencies
@@ -276,7 +276,7 @@
This package is intended to run on all major OS, this includes Windows (latest version), MacOS (latest) and the latest version of Linux (Ubuntu).
Similarly it also tested on python 3.8, and 3.9.
Please note these are only the systems this package is being actively tested on, if you run on a similar system (e.g. an earlier version of Linux) this package
@@ -284,7 +284,7 @@
spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from the
Huggingface model hub
in your spaCy pipeline allowing inclusion of existing models within SpaCy workflows.
To ask report issues or request features, please use the
GitHub Issue Tracker.
Questions related to SpaCy are kindly referred to the SpaCy GitHub or forum. Otherwise,
@@ -270,7 +270,7 @@
Spacy-wrap modifies pre-existing code from spacy-transformers and thus a large part of
the credit goes to the Explosion team. Similarly, the library utilizes models available
on the Huggingface Hub, thus wrapped pipelines should be attributed to the respective
@@ -286,7 +286,7 @@
SpaCy-wrap currently includes only two pipeline component the
"sequence_classification_transformer" for sequence classification and
the "token_classification_transformer" for token classification or named
@@ -244,10 +244,10 @@
Construct a SequenceClassificationTransformer component, which lets you
plug a model from the Huggingface transformers library into spaCy so you
can use it in your pipeline. The component will add a Doc extension with
@@ -311,10 +311,10 @@
Construct a ClassificationTransformer component, which lets you plug a
model from the Huggingface transformers library into spaCy so you can use
it in your pipeline. One or more subsequent spaCy components can use the
@@ -466,9 +466,9 @@