This repository provides code examples and supplementary materials for the book "Practical PyTorch Model Training." It targets individuals learning PyTorch for deep learning, offering practical applications and deployment frameworks for Computer Vision, Natural Language Processing, and Large Language Models.

How It Works

The project is structured around the book's chapters, with each directory containing code snippets and scripts for specific topics. It demonstrates core PyTorch functionalities, model training techniques, and integrates with deployment tools like ONNX and TensorRT, providing a hands-on learning experience.

Quick Start & Requirements

• Install dependencies: pip install -r requirements.txt
• Manually install PyTorch and Torchvision (CPU versions recommended): https://pytorch.org/get-started/locally/
• Tested environments: Windows 10 (Python 3.5, PyTorch 0.4.0) and macOS (Python 3.6, PyTorch 0.4.1/1.0.0).

Highlighted Details

• Second edition includes over ten practical projects covering CV, NLP, and LLM applications.
• Features tutorials on ONNX and TensorRT for inference deployment.
• Code is designed to complement the "Practical PyTorch Model Training" book.

Maintenance & Community

• Active community support via QQ groups (multiple groups are listed, with the latest being group 5: 1021300804).
• Contact email for feedback: yts3221@126.com.

Licensing & Compatibility

• The repository itself does not explicitly state a license. The book's licensing is not detailed in the README.

Limitations & Caveats

The provided environment configurations (PyTorch 0.4.0/1.0.0) are significantly outdated, which may lead to compatibility issues with current PyTorch versions and libraries. The README does not specify a license, which could impact commercial use or integration into proprietary projects.