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: :doc:`tutorial_wordembed` .
Q3. Can this package work on Python 2?
Ans: No.
Q4. Warning or messages pop up when running models involving neural networks. What is the problem?
Ans: Make sure your keras have version >= 2.
Q5. 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.
Q6. Is there any reasons why word-embedding keras layers no longer used since release 0.5.11?
Ans: This functionality is removed since release 0.5.11, due to the following reasons:
- keras changed its code that produces this bug;
- the layer is consuming memory;
- only Word2Vec is supported; and
- the results are incorrect.
Q7. 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.
**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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