Skip to main content

Wrappers for scikit-learn and PyTorch models with OpenVINO optimization

Project description

OpenVino training kit

Wrappers for scikit-learn and PyTorch models with OpenVINO optimization.

About

This module provides easy-to-use wrappers for training, evaluating, and exporting classical (scikit-learn) and deep learning (PyTorch) models optimized for OpenVINO, targeting local AI PCs and edge deployment.

System Requirements

  • Operating System: Linux (Ubuntu 18.04+), Windows 10/11, Windows Server 2019+
  • CPU: x86-64 (Intel or AMD)
  • Python: 3.8, 3.9, 3.10, 3.11
  • RAM: 8GB+ recommended
  • GPU: Optional (not required)
  • Note: Intel Extension for PyTorch (IPEX) is only supported on Linux/Windows with x86-64 CPUs. On MacOS, some features may not be available.

Installation

pip install ov-training-kit

Usage

For detailed usage instructions and examples, please refer to the README files inside the src/sklearn and src/pytorch folders.


For questions, suggestions, or contributions, feel free to open an issue or pull

🎓 Credits & License

Developed as part of a GSoC

Authors

  • Leonardo Heim
  • Shivam Basia

Project details


Download files

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

Source Distribution

ov_training_kit-0.1.3.tar.gz (13.3 kB view details)

Uploaded Source

Built Distribution

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

ov_training_kit-0.1.3-py3-none-any.whl (15.5 kB view details)

Uploaded Python 3

File details

Details for the file ov_training_kit-0.1.3.tar.gz.

File metadata

  • Download URL: ov_training_kit-0.1.3.tar.gz
  • Upload date:
  • Size: 13.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.7

File hashes

Hashes for ov_training_kit-0.1.3.tar.gz
Algorithm Hash digest
SHA256 a6ae3ad59e4c093fdda321c86866c57bbaf56329f8308618640f4b8ac0bd1cda
MD5 de8e7915e2174db955575bf1ed8527ea
BLAKE2b-256 9786e081ea412c44375401bee92fb174bfdb1bb8fdc438e07b3a775e05ca2eac

See more details on using hashes here.

File details

Details for the file ov_training_kit-0.1.3-py3-none-any.whl.

File metadata

File hashes

Hashes for ov_training_kit-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 4bfbe09361cd0167b84af51a59d626e1653b8c224174ed61fb638b4c6de3182b
MD5 b15164a4ef763454c6ab39e7c84a9bd3
BLAKE2b-256 24b1ce0b23f6a46feb96edc35c9838963c733446bda90590a9462c42f64e03a3

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