PyTorch: Difference between revisions
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PyTorch<ref name="PyTorch"/> is a Python-based, open source, and production-ready AI framework that supports distributed training, graph mode, and cloud platforms. | PyTorch<ref name="PyTorch"/> is a Python-based, open source, and production-ready AI framework that supports distributed training, graph mode, and cloud platforms. | ||
PyTorch packages can be installed and managed using Conda. Conda-forge's Miniforge<ref name="Miniforge"/> is an open-source application that allows you to create and manage conda environments. | |||
Trained PyTorch Models can be exported using the [[ONNX]] file format, which in turn can be imported into the {{software}} as a [[Neural Network]] for an [[Inference Overlay]]. | |||
{{article end | {{article end | ||
Revision as of 12:57, 14 October 2025
PyTorch[1] is a Python-based, open source, and production-ready AI framework that supports distributed training, graph mode, and cloud platforms.
PyTorch packages can be installed and managed using Conda. Conda-forge's Miniforge[2] is an open-source application that allows you to create and manage conda environments.
Trained PyTorch Models can be exported using the ONNX file format, which in turn can be imported into the Tygron Platform as a Neural Network for an Inference Overlay.
How-to's
- How to export AI Training Data
- How to train your own AI model for an Inference Overlay
- How to import an ONNX file using drag and drop
- How to import an ONNX file for an Inference Overlay
- How to adjust a Neural Networks metadata
See also
References
- ↑ PyTorch ∙ found at: https://pytorch.org/ (last visited: 2025-02-04)
- ↑ Miniforge ∙ found at: https://conda-forge.org/download/ (last visited: 2025-10-13)