#tensor library

Access extensive deep learning documentation with PyTorch Chinese translations, offering optimized use for both GPU and CPU. Engage with the community to explore translated PyTorch 2.0 resources, and visit official sites for continuous updates. This initiative promotes the open dissemination of knowledge and encourages collaborative participation to enhance resource quality. Join the conversation through various platforms for feedback and contributions.

Discover a versatile tensor library designed for seamless machine learning on multiple platforms. With features like integer quantization and broad hardware compatibility, it supports efficient model training using ADAM and L-BFGS optimizers. Benefit from zero memory allocations during runtime for enhanced performance. Easily build on platforms such as Android and leverage CUDA and SYCL for GPU acceleration. See its capabilities in action with examples of GPT inference. Stay updated to harness the library's expanding features and improved functionality.