Frequently Asked Questions (FAQ)

Q1. Can we use backends other than TensorFlow?

Ans: No.

Q2. Can we use word-embedding algorithms other than Word2Vec?

Ans: Yes. Besides Word2Vec, you can use FastText and Poincaré embedding. See: Word Embedding Models .

Q3. Can this package work on Python 2?

Ans: No.

Q4. How should I cite `shorttext` if I use it in my research?

Ans: For the time being, You do not have to cite a particular paper for using this package. However, if you use any particular functions or class, check out the docstring. If there is a paper (or papers) mentioned, cite those papers. For example, if you use CNNWordEmbed in frameworks, according to the docstring, cite Yoon Kim’s paper. Refer to this documentation for the reference too.

Q5. I am having trouble in install `shorttext` on Google Cloud Platform. What should I do?

Ans: There is no “Python.h”. Run: sudo apt-get install python3-dev in SSH shell of the VM instance.

**Q6. Where is the Sakiguchi spell corrector? **

Ans: It was removed since release 3.0.0, but you can refer to the `examples` folder in the Github repository for the codes.

Q7. Where are `WrappedBERTEncoder` and `BERTScorer`?

Ans: It was removed since release 3.0.0, but you can install another package shorttext-bert to get the same functionality.

**Q8. My model files were created by shorttext version < 2.0.0. How do I make them readable for version >= 2.0.0?

Ans: Simply make those files with names ending with .h5 to .weights.h5.

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