jcjohnson/torch-rnn

Health v2 · maintenance only

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Adoption not part of the score

2559 stars · 508 forks observed · 2026-08-28

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

torch-rnn provides high-performance, reusable RNN and LSTM modules for the Torch7 deep learning framework, used for character-level language modeling similar to char-rnn. It is significantly faster and more memory-efficient than char-rnn while having minimal dependencies.

Use cases

• train a character-level language model
• run an RNN or LSTM in torch7
• generate text with a char-rnn style model
• benchmark LSTM implementations for speed and memory
• integrate reusable RNN modules into an existing torch project

When to choose

• you are already working in the Torch7 ecosystem and need efficient RNN/LSTM modules
• you want a faster, lower-memory alternative to char-rnn
• you need GPU acceleration via CUDA or OpenCL for recurrent models

When to avoid

• you are starting a new project - modern frameworks like PyTorch or TensorFlow are actively maintained instead
• you need transformer-based or large language model tooling
• you require long-term support, as Torch7 is a legacy framework

Facets

library · maturity maintenance

machine-learning deep-learning llm-training benchmarking deep-learning machine-learning lua rnn lstm torch7 char-rnn language-modeling cuda opencl natural-language-processing linux macos gpu docker

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