How to fix spaCy en_training incompatible with current spaCy version
Question:
UserWarning: [W094] Model 'en_training' (0.0.0) specifies an under-constrained spaCy version requirement: >=2.1.4.
This can lead to compatibility problems with older versions,
or as new spaCy versions are released, because the model may say it's compatible when it's not.
Consider changing the "spacy_version" in your meta.json to a version range,
with a lower and upper pin. For example: >=3.2.1,<3.3.0
spaCy version 3.2.1
Python version 3.9.7
OS Window
Answers:
For spacy v2 models, the under-constrained requirement >=2.1.4 means >=2.1.4,<2.2.0 in effect, and as a result this model will only work with spacy v2.1.x.
There is no way to convert a v2 model to v3. You can either use the model with v2.1.x or retrain the model from scratch with your training data.
pip3 install spacy==2.1.4
This can download required
UserWarning: [W094] Model 'en_training' (0.0.0) specifies an under-constrained spaCy version requirement: >=2.1.4.
This can lead to compatibility problems with older versions,
or as new spaCy versions are released, because the model may say it's compatible when it's not.
Consider changing the "spacy_version" in your meta.json to a version range,
with a lower and upper pin. For example: >=3.2.1,<3.3.0
spaCy version 3.2.1
Python version 3.9.7
OS Window
For spacy v2 models, the under-constrained requirement >=2.1.4 means >=2.1.4,<2.2.0 in effect, and as a result this model will only work with spacy v2.1.x.
There is no way to convert a v2 model to v3. You can either use the model with v2.1.x or retrain the model from scratch with your training data.
pip3 install spacy==2.1.4
This can download required