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A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
A collection of infrastructure and tools for research in neural network interpretability and visualization.
A collection of interactive machine learning experiments with Jupyter notebooks for training and browser demos for visualization.
A Swift kernel for Google Colaboratory that enables Swift programming in the browser with GPU support for machine learning.
A Python script for parallel multi-threaded file transfers in Google Colab, achieving 10-50x speed improvements.
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