Ákos Kádár by kadarakos
Description: Thinc is a lightweight type-checked deep learning library for composing models, with support for layers defined in frameworks like PyTorch and TensorFlow.
A refreshing functional take on deep learning, compatible with your favorite libraries. from the makers of spaCy & Prodigy 🔮 Use any framework Switch between PyTorch, TensorFlow and MXNet models without changing your application, or even create mutant hybrids using zero-copy array interchange.
🚀 Type checking Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers.
Configuration is a major pain for ML. Thinc lets you describe trees of objects with references to your own functions, so you can stop passing around blobs of settings. It's simple, clean, and it works for both research and production.
Ákos Kádár by kadarakos