Machine learning framework
Provides the framework used to develop and run machine learning models.
An open-source machine learning framework for building and running AI models.
PyTorch is an open-source machine learning framework used to build and run AI models. It provides a foundation for model development and connects workloads to device, memory-allocation, stream, and compiler abstractions. The project’s ecosystem includes model implementations and work on native device support, making PyTorch relevant to both model developers and teams adapting compute hardware to the framework.
Provides the framework used to develop and run machine learning models.
PyTorch's device abstractions can be used to connect hardware backends to framework workloads.
Allocator and stream abstractions are part of the interfaces used when integrating a native device.
Compiler abstractions provide another integration point for hardware implementations.
The official site indexes model implementations, including transformer and computer-vision models.
Use PyTorch as the framework foundation for creating and running AI models.
Hardware teams can connect device, allocator, stream, and compiler components to make a device usable through PyTorch.
Developers can review indexed implementations such as transformers, object detection, image generation, and image classification models.
PyTorch is an open-source machine learning framework for building and running AI models.
The official materials describe native device integration through PyTorch device, allocator, stream, and compiler abstractions.
The official site indexes model implementations, including transformer, object detection, image generation, and image classification examples.
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