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Python 15.71% Jupyter Notebook 84.29%
lstm generator rnn keras tensorflow synopsis films genres beam-search

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films-synopsis-generator's Issues

Report statistics about the dataset

It would be nice to generate some statistics about the dataset. E.g.

  • distribution of genres
  • synopsys lengths (considering that we define our constant MAX_SYNOPSIS_LEN)
  • (maybe using a python notebook)
    Feel free to post some ideas

Make predicitons (generate synopsis)

Now that we have some trained weights, we should code the functions necessary to load them into the model and make actual predictions. Goal is to be able to check whether the generated synopsis start to make sense or not.

This code should be useful for doing so

Find out how to include pretrained word embeddings in the training

So far the network is not using any word embeddings like word2vec or GloVe. It could be interesting to compare results of that baseline against a net that makes use of them. I haven't figured out how to make them, basically because I used a lot of the code from this repo and he doesn't use it, although in the README.md says that Pre-trained word embeddings can also be used..

This is the best spanish pretrained word embedding model that I have found, so I think we should use them.

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