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thinc

Functional deep learning library with NumPy and PyTorch integration

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A refreshing functional take on deep learning, compatible with your favorite libraries

Commands

thinc

Examples

Import and create a simple neural network layer$ python -c "from thinc.api import chain, with_array; print('Thinc imported successfully')"

Use Thinc for model composition with functional approach$ python -c "from thinc.api import Model, Relu, Softmax; model = chain(Relu(nO=64), Softmax()); print(model)"

Initialize and configure a Thinc model for training$ python -c "from thinc.api import Config; config = Config().from_str(''); print('Config loaded')"