Project setup
run command to setup assets(dataset from UD)
spacy project assets
It uses project.yml file and download the data from UD GitHub repository.
Download vectors
Download fasttext vectors
wget https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.ur.300.vec.gz
Use these vectors to prune it so that model size is reduced. I’m currently using 100000 vectors for training the model.
mkdir vectors
python -m spacy init vectors ur cc.ur.300.vec.gz ./vectors --truncate 100000 --name ur_model.vectors
Train the model
Now run the command to train the tagger and parser for Urdu language.
spacy project run all
It will train the tagger and parser model on cpu. You can specify gpu in project.yml file.
Install the model
After training, you can install and use the model.
pip install ur_model-0.0.0.tar.gz
There is a script test.py on how to use the model.
