This repository provides the second edition of a comprehensive PyTorch tutorial, aimed at individuals from beginners to experienced engineers. It covers foundational PyTorch concepts, advanced applications in Computer Vision (CV), Natural Language Processing (NLP), and Large Language Models (LLMs), and concludes with practical deployment strategies, enabling users to build and deploy deep learning models effectively.

How It Works

The tutorial is structured into three parts: "PyTorch Basics" for foundational knowledge, "Industry Applications" for practical use cases in CV, NLP, and LLMs, and "Industrial Deployment" for model optimization and serving. It emphasizes a hands-on approach, integrating theoretical explanations with extensive code examples and project-based learning. The content progresses from core PyTorch modules to complex model architectures and deployment frameworks like ONNX and TensorRT.

Quick Start & Requirements

• Online Reading: 《PyTorch实用教程》（第二版）
• Companion Code: 《PyTorch实用教程》（第二版）
• Prerequisites: Python, PyTorch. Specific hardware requirements (e.g., GPU) may be necessary for certain advanced examples.

Highlighted Details

• Covers 8 CV tasks (classification, segmentation, detection, etc.) and 5 NLP tasks (text classification, machine translation, etc.).
• Includes detailed analysis and application of LLMs like Qwen, ChatGLM, Baichuan, and Yi.
• Provides practical guidance on model deployment using ONNX and TensorRT, including quantization techniques (PTQ, QAT).
• Offers a systematic learning path from basic PyTorch usage to end-to-end project implementation.

Maintenance & Community

• The project has multiple QQ groups for reader interaction, with several groups already at capacity, indicating active community engagement.
• Recent updates and technical articles on CV, LLM deployment, and RAG systems are shared within the community.

Licensing & Compatibility

• License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
• Restrictions: This license prohibits commercial use. Compatibility with closed-source projects may be restricted due to the non-commercial clause.

Limitations & Caveats

The "NonCommercial" clause in the CC BY-NC 4.0 license strictly prohibits any commercial use of the tutorial's content or associated code. The project has experienced significant periods of inactivity due to the author's personal and professional commitments.