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-0.9.0-py3-none-any.whl (204.4 kB view details)

Uploaded Python 3

File details

Details for the file macboost-0.9.0-py3-none-any.whl.

File metadata

  • Download URL: macboost-0.9.0-py3-none-any.whl
  • Upload date:
  • Size: 204.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.6

File hashes

Hashes for macboost-0.9.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a1d8fe3a94114a166c9b8f5c843e48b2589e113959f608c5bd146f73919fea6e
MD5 5dacd48e1c998d3e734f33e9fe92c7bb
BLAKE2b-256 152b1e625f2e0f5d141389ddb17a677a58f0da008f0992ed2f5f2a27b0baa2a5

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