DEPRECATION WARNING

IF YOU ARE INTERESTED IN A MORE RECENT PROJECT ON USING FASTTEXT VECTORS IN RASA, TRY THE FOLLOWING CODE https://github.com/RasaHQ/rasa-custom-fasttext

Credits to: https://github.com/koaning

THIS CODE BASE IS NOT MAINTAINED FOR OVER 3 YEARS. Life goes on!!

Loading FastText vectors on Spacy

Tbe requirements are really simple.

Requirements

You should have docker

Download the FastText vector

In order to build with fastText, first download the FastText vector you need in the langauge from here

FastText Pre-trained vectors

Load the vectors

Save the downloaded vector file in vector folder.

Build with docker

Build the docker file as

docker build -t spacy-fasttext .

Train your first model

Once the image is built, run the following command to build the first model Go to terminal and reach the present directory first.

docker run -v $PWD:/app spacy-fasttext python load_fastText.py 

This will build the model in the model folder

Package your model

docker run -v $PWD:/app spacy-fasttext python -m spacy package model model_package

docker run -it -v $PWWD::/app spacy-fasttext bash
cd model_package/nl_model-0.0.0
python setup.py sdist

This will then export a packaged model in .tar.gz, when then you can load for your NLP purposes.