Practical PyTorch Tutorial (Second Edition)
A Chinese-language PyTorch tutorial, in a second edition, covering PyTorch fundamentals, computer vision, NLP and large-model applications, plus inference deployment with ONNX and TensorRT and companion example code.
This is the second edition of a Chinese-language practical PyTorch tutorial, expanded from the first edition with deep-learning application case studies and inference-deployment frameworks. It is organized into three parts: PyTorch fundamentals for beginners, covering the framework's data, model, optimization and visualization modules; industry applications, covering computer-vision tasks such as classification, segmentation, detection, tracking and image generation, NLP tasks such as translation and named-entity recognition using RNNs, Transformers, BERT and GPT, and large-language-model deployment and analysis for models including Qwen, ChatGLM, Baichuan and Yi.
The final part covers deploying trained models into production, explaining ONNX and TensorRT and quantization methods such as PTQ and QAT. The tutorial is free and available online, with companion example code and notebooks for each chapter.