farizrahman4u/seq2seq

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3169 stars · 829 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A sequence-to-sequence learning add-on library for Keras, providing modular encoder-decoder layers and ready-made Seq2Seq models. It supports deep stacked LSTMs, attention mechanisms, and building models that can be used standalone or as layers in larger networks.

Use cases

• build sequence-to-sequence models in Keras
• train a machine translation model
• create a chatbot with an encoder-decoder network
• implement attention-based seq2seq models
• build a neural parser for sequences
• stack LSTM layers for encoder and decoder

When to choose

• you are using Keras and need seq2seq models with reusable encoder/decoder layers
• you want ready-made SimpleSeq2Seq or attention-based models out of the box
• you need to embed seq2seq components as layers inside a larger Keras model

When to avoid

• you are using PyTorch, TensorFlow 2.x/Keras 3, or another framework instead of legacy Keras
• you need actively maintained code with recent updates and support
• you want modern transformer-based sequence models

Facets

library · maturity maintenance

deep-learning machine-learning nlp machine-learning deep-learning python seq2seq keras encoder-decoder attention machine-translation neural-networks natural-language-processing

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markdown · JSON · MCP: product_card(name="farizrahman4u/seq2seq")