# google/seq2seq

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5,621 stars · 1,291 forks · Python · Apache-2.0 · archived

## Links

- GitHub: https://github.com/google/seq2seq
- Homepage: https://google.github.io/seq2seq/
- awesome-repositories: https://awesome-repositories.com/repository/google-seq2seq.md

## Topics

`deeplearning` `machine-translation` `neural-network` `tensorflow` `translation`

## Description

This is a TensorFlow-based encoder-decoder framework and model library used for mapping input sequences to output sequences. It functions as a deep learning sequence mapper designed to transform sequential data from one domain to another.

The library provides tools for implementing sequence-to-sequence modeling across multiple domains, including neural machine translation, automatic text summarization, and image captioning generation.

The framework incorporates recurrent neural networks and utilizes attention-based contextualization to weight input sequences. It supports multiple decoding strategies, including beam search and greedy decoding, while executing mathematical operations via TensorFlow graph computation.

## Tags

### Artificial Intelligence & ML

- [Encoder-Decoder Architectures](https://awesome-repositories.com/f/artificial-intelligence-ml/encoder-decoder-architectures.md) — Provides a comprehensive encoder-decoder framework for mapping input sequences to output sequences.
- [Sequence Mappers](https://awesome-repositories.com/f/artificial-intelligence-ml/deep-learning-architectures/sequence-mappers.md) — Functions as a deep learning sequence mapper for transforming sequential data across domains.
- [Recurrent Neural Networks](https://awesome-repositories.com/f/artificial-intelligence-ml/recurrent-neural-networks.md) — Utilizes recurrent neural networks to maintain memory of previous tokens in variable length text streams.
- [Sequence-to-Sequence Mappings](https://awesome-repositories.com/f/artificial-intelligence-ml/sequence-decoding-models/sequence-to-sequence-mappings.md) — Maps input sequences to target sequences via latent representations for tasks like translation and summarization. ([source](https://cdn.jsdelivr.net/gh/google/seq2seq@master/README.md))
- [TensorFlow Model Development](https://awesome-repositories.com/f/artificial-intelligence-ml/tensorflow-model-development.md) — Built as a framework for developing and training sequence-to-sequence models using the TensorFlow ecosystem.
- [Input Sequence Attentions](https://awesome-repositories.com/f/artificial-intelligence-ml/attention-mechanisms/input-sequence-attentions.md) — Implements attention weights on input sequences to provide necessary context for the decoder during sequence generation.
- [Image Description Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/image-description-generation.md) — Generates descriptive text labels for images by mapping visual data to natural language.
- [Beam Search Implementations](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-deployment-and-serving/inference-optimization-and-tuning/decoding-strategies/beam-search-implementations.md) — Provides beam search decoding to explore multiple candidate sequences for optimal probability outcomes.
- [Neural Machine Translation](https://awesome-repositories.com/f/artificial-intelligence-ml/neural-machine-translation.md) — Provides neural machine translation capabilities to translate text between natural languages.
- [Greedy Decoding Strategies](https://awesome-repositories.com/f/artificial-intelligence-ml/sequence-decoding-models/sequence-decoders/greedy-decoding-strategies.md) — Includes a greedy decoding strategy that selects the highest probability token at each step.
- [TensorFlow Graph Execution](https://awesome-repositories.com/f/artificial-intelligence-ml/tensorflow-graph-execution.md) — Executes mathematical operations via TensorFlow's static computational graphs for efficient GPU and CPU processing.
- [Text Summarization](https://awesome-repositories.com/f/artificial-intelligence-ml/text-summarization.md) — Enables automatic text summarization by condensing long documents while retaining key information.

### Part of an Awesome List

- [Sequence To Sequence Models](https://awesome-repositories.com/f/awesome-lists/ai/sequence-to-sequence-models.md) — Provides a comprehensive library of tools for training sequence-to-sequence models.
- [Generative Models](https://awesome-repositories.com/f/awesome-lists/ai/generative-models.md) — Large-scale neural machine translation architecture implementation.
- [Natural Language Processing](https://awesome-repositories.com/f/awesome-lists/ai/natural-language-processing.md) — Encoder-decoder framework for TensorFlow.