clab/dynet

Health v2 · maintenance only

Adoption not part of the score

3436 stars · 701 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

DyNet is a C++ neural network toolkit with Python bindings, designed for efficient CPU/GPU training of networks with dynamic per-instance structure. It features auto-batching and has powered NLP systems for parsing, machine translation, and morphological inflection.

Use cases

• build neural networks with dynamic computation graphs
• train NLP models like parsers and machine translation systems
• run deep learning efficiently on CPU or GPU
• auto-batch many small training examples for speed
• prototype research models in Python or C++

When to choose

• your model's graph structure changes per training instance
• you need fast auto-batched training for NLP research
• you want a lightweight C++ deep learning library with Python bindings

When to avoid

• you need a large ecosystem of pretrained models and tools
• you want mainstream community support like PyTorch or TensorFlow
• the project's low recent activity is a concern for long-term use

Facets

library · maturity maintenance

machine-learning deep-learning nlp machine-learning deep-learning cpp python windows dynamic-computation-graph auto-batching neural-networks tensor-library natural-language-processing linux macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="clab/dynet")