Skip to main content

Gradient boosted trees on Apple-silicon GPUs (Metal), sklearn-style API

Project description

macboost (Python)

Python bindings for MacBoost — gradient boosted trees on Apple-silicon GPUs, with a scikit-learn-style API (MacBoostRegressor, MacBoostClassifier).

Build the native core first, then install:

swift build -c release && ../scripts/build_python.sh   # bundles the dylib
pip install .

See the repository README for usage and benchmarks.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

macboost-0.3.0-py3-none-any.whl (168.8 kB view details)

Uploaded Python 3

File details

Details for the file macboost-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: macboost-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 168.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.6

File hashes

Hashes for macboost-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 fa83bb2fd92a3396cd6b9457ce7e1947380d5a341c246063f94f120c32acbafd
MD5 ffac261e218cb217465c11eb6341cb60
BLAKE2b-256 f50d5f2401b5513521a7bfaa3b8b690c86ec24ebcf0afae6b9ee61b34990b805

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page