joserapa98/tensorkrowch
Smooth integration of tensor networks in machine learning
TensorKrowch helps machine learning researchers and practitioners integrate tensor networks into deep learning pipelines. It allows you to build, train, and experiment with various tensor network architectures, taking raw data inputs and producing trained models or insights into suitable network designs. This is for users familiar with PyTorch who want to explore tensor networks for their machine learning tasks.
Available on PyPI.
Use this if you want to rapidly prototype and test different tensor network configurations within a PyTorch environment to find the most effective model for your data.
Not ideal if your primary concern is the absolute fastest training performance for an already optimized tensor network, as dedicated implementations might be quicker.
Stars
49
Forks
2
Language
Python
License
MIT
Category
Last pushed
Feb 18, 2026
Commits (30d)
0
Dependencies
2
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