farizrahman4u/seq2seq
A Keras add-on for building and training sequence-to-sequence neural network models.
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Seq2Seq provides modular, reusable layers and built-in models for seq2seq learning with Keras. It implements encoder-decoder architectures where the encoder converts an input sequence to a context vector and the decoder generates the output sequence. The library supports stacked LSTMs on both encoder and decoder sides, customizable depth, and can be integrated as layers into larger models for tasks like machine translation, chatbot development, and parsing.
Frequently asked
- What is farizrahman4u/seq2seq?
- A Keras add-on for building and training sequence-to-sequence neural network models.
- Is seq2seq open source?
- Yes — farizrahman4u/seq2seq is open source, released under the GPL-2.0 license.
- What language is seq2seq written in?
- farizrahman4u/seq2seq is primarily written in Python.
- How popular is seq2seq?
- farizrahman4u/seq2seq has 3.2k stars on GitHub.
- Where can I find seq2seq?
- farizrahman4u/seq2seq is on GitHub at https://github.com/farizrahman4u/seq2seq.