microsoft / hummingbird
Hummingbird compiles trained ML models into tensor computation for faster inference.
Why this job: matched by what the repo talks about: inference, model, faster, train
What it does
Currently, you can use *Hummingbird* to convert your trained traditional ML models into PyTorch, TorchScript, ONNX, and TVM). *Hummingbird* supports a variety of ML models and featurizers. These models include scikit-learn Decision Trees and Random Forest, and also LightGBM and XGBoost Classifiers/Regressors. Support for other neural network backends and models is on our roadmap.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 57 days ago
- Stars
- 3,553
- +1 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.4.12
- Released 2 years ago
- Built with
- Python
- 88% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 80% closed
- 67 still open
- Pull requests
- 425 merged
- 15 waiting
- Releases
- 25
- 0 in the last year
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More: languages, topics and project record
Languages
- Python 88%
- Jupyter Notebook 11%
- Makefile 1%
- JavaScript <1%
Topics
- machine-learning
- neural-networks
- scikit-learn
- pytorch
- tensor-computation
Project record
- JobLocal LLMs
- StatusListed
- Commits482
- Forks294
- Watching50
- Stars in 28 days+6
- CreatedMar 12, 2020
- First seen by usNov 7, 2026
- CheckedNov 8, 2026