Thinc
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About
Thinc offers a refreshing and functional approach to deep learning, designed to be compatible with your favorite libraries such as PyTorch, TensorFlow, and MXNet. It allows seamless switching between frameworks and even the creation of "mutant hybrids" using zero-copy array interchange. The library emphasizes developer efficiency with sophisticated type checking that catches bugs early, even as code is being written. Thinc also addresses the common pain point of ML configuration by providing a clean way to describe trees of objects with references to custom functions, suitable for both research and production. It is super lightweight, easy to install via pip and conda on various operating systems, and has very few dependencies. Though its redesign is new, previous versions have been powering spaCy, making Thinc a battle-tested solution in thousands of companies. Its innovative design reflects the latest advancements in neural networks and Python.
Platform
Task
Features
• innovative design
• battle-tested
• super lightweight
• awesome config
• type checking
• use any framework
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