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Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to seamlessly leverage neural network frameworks (such as PyTorch) to accelerate traditional ML models. Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of this (4) without having to re-engineer their models.
Features
- Hummingbird works by reconfiguring algorithmic operators
- Documentation available
- Examples available
- Once PyTorch is installed, you can get Hummingbird from pip
- Hummingbird was tested on Python 3.9, 3.10 and 3.11
- For Linux, Windows and MacOS
Project Samples
Categories
Machine LearningLicense
MIT LicenseFollow Hummingbird
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