salesforce/pytorch-qrnn

Health v2 · maintenance only

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1263 stars · 192 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of the Quasi-Recurrent Neural Network (QRNN) from Salesforce Research, offering LSTM-like accuracy with 2-17x faster training than cuDNN LSTM. It provides a drop-in replacement API for PyTorch's LSTM/GRU modules with both GPU and CPU implementations.

Use cases

• speed up LSTM training in PyTorch
• replace LSTM or GRU layers with a faster recurrent network
• train language models faster with AWD-QRNN
• run recurrent networks across multiple GPUs with DataParallel
• build sequence models with fewer compute costs

When to choose

• you need faster recurrent network training than cuDNN LSTM on NVIDIA GPUs
• you want a drop-in LSTM/GRU replacement in PyTorch with similar accuracy
• you are doing language modeling and want near state-of-the-art results with quicker training

When to avoid

• you need bidirectional recurrent layers (not supported)
• you work only on CPU where speedups are smaller
• you need actively maintained code with recent PyTorch compatibility
• you prefer transformer-based architectures over RNNs

Facets

library · maturity maintenance

machine-learning deep-learning machine-learning deep-learning python cross-platform pytorch qrnn quasi-recurrent-neural-network lstm-alternative rnn cuda language-modeling natural-language-processing gpu linux

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