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Text-Summarization

The objective of this project is to build a seq2seq model that can create relevant summaries. The dataset contains above 500,000 reviews, and is hosted on Kaggle. It's too large to host here, it's over 300MB.

To build model use a two-layered bidirectional RNN with LSTMs on the input data and two layers, each with an LSTM using bahdanau attention on the target data. This model uses Conceptnet Numberbatch's pre-trained word vectors.

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