facebookarchive/MemNN

Health v2 · maintenance only

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Adoption not part of the score

1753 stars · 368 forks observed · 2026-10-14

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

Facebook AI Research's reference implementations of memory-augmented neural networks (MemN2N, Key-Value Memory Networks, Entity Networks) written in Lua/Torch7 and Matlab. It accompanies several research papers on end-to-end memory networks, bAbI tasks, and dialogue-based learning.

Use cases

• implement end-to-end memory networks for question answering
• run MemN2N experiments on bAbI tasks
• train key-value memory networks for document reading
• study dialogue-based language learning models
• reproduce research results from memory network papers

When to choose

• you need reference implementations of MemN2N or Entity Networks from the original papers
• you are doing research on memory-augmented neural architectures
• you work with Torch7/Lua and want historical FAIR code

When to avoid

• you need a maintained or production-ready library
• you want modern PyTorch or TensorFlow implementations
• you are not familiar with the deprecated Torch7 framework

Facets

library · maturity abandoned

machine-learning deep-learning nlp rag machine-learning deep-learning artificial-intelligence lua memory-networks memn2n torch7 babi research-code facebook-archive natural-language-processing linux macos

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