lmnt-com/haste

Haste: a fast, simple, and open RNN library

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Emerging

This project provides highly optimized building blocks for deep learning models that process sequential data like audio, text, or sensor readings. It allows machine learning engineers and researchers to quickly integrate state-of-the-art recurrent neural network (RNN) layers into their TensorFlow or PyTorch projects. You provide your sequential data, and the layers output processed representations, enabling faster development of high-performance models for tasks like speech recognition or natural language understanding.

336 stars. No commits in the last 6 months.

Use this if you are a machine learning engineer or researcher developing models that rely on recurrent neural networks (RNNs) and need to maximize their performance and efficiency on NVIDIA GPUs.

Not ideal if you are new to deep learning or only require basic RNN functionality without advanced performance tuning or GPU acceleration.

deep-learning recurrent-neural-networks sequential-data-processing gpu-acceleration machine-learning-engineering
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

336

Forks

31

Language

C++

License

Apache-2.0

Last pushed

Jul 18, 2023

Commits (30d)

0

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