Czech image captioning, machine translation, sentiment analysis and summarization (Neural Monkey models)

These models are for the [Neural Monkey](https://ufal.mff.cuni.cz/neuralmonkey) toolkit for Czech and English, solving four NLP tasks: machine translation, image captioning, sentiment analysis, and summarization. The models are trained on standard datasets and achieve state-of-the-art or near state-of-the-art performance in the tasks. The same models can also be invoked via [an online demo](https://ufal.mff.cuni.cz/grants/lsd).
This entry also includes models for automatic news summarization for Czech and English. The Czech models were trained using the [SumeCzech dataset](http://hdl.handle.net/11234/1-2615), while the English models were trained using the [CNN-Daily Mail](https://paperswithcode.com/dataset/cnn-daily-mail-1) corpus, using the standard recurrent sequence-to-sequence architecture.
The models are available for download from the LINDAT repository.