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PyG is a library built upon PyTorch to easily write and train Graph Neural Networks for a wide range of applications related to structured data. PyG is both friendly to machine learning researchers and first-time users of machine learning toolkits.
Free Image Generation on Pyg.ai (Beta) : r/pyg_ai - Reddit
New users can generate 25 images for free right after signing up! Current features are: Bulk image generation with Prompting + Negative Prompting. Image search & storage, whatever you generate stays until you delete it. Get inspired by browsing content other users have made and clicking it to edit yourself.
pyg-team/pytorch_geometric - GitHub
The PyG engine utilizes the powerful PyTorch deep learning framework with full torch.compile and TorchScript support, as well as additions of efficient CPU/CUDA libraries for operating on sparse data, e.g., pyg-lib. The PyG storage handles data processing, transformation and …
PyG Documentation — pytorch_geometric documentation
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers.
Accelerating PyG on NVIDIA GPUs
Sep 22, 2022 · Developers and researchers can take advantage of NVIDIA AI for significantly faster model training, which unlocks the ability to perform Graph Neural Network (GNN) training workflows right in the PyG framework with no line of code change.
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Open-source AI project for chat, role-play, adventure, and more!
pyg_ai - Reddit
pyg_ai Official communitty page for pyg.ai. Share pictures you've made on Pyg.ai, discuss issues you've had with prompting, provide feedback and suggestions.
PyG · GitHub
Graph Neural Network Library for PyTorch. PyG has 5 repositories available. Follow their code on GitHub.
Webinar - PyG
Mar 7, 2023 · You’ll see a deep dive from the core team and industry leaders on how to effectively build, manage, and scale your graph to production use cases. You’ll learn how to quickly operationalize Graph Neural Networks into existing workflows and generate highly optimized and custom embeddings for your use case. You can read more about the ...
pyg-team pytorch_geometric · Discussions · GitHub
Explore the GitHub Discussions forum for pyg-team pytorch_geometric. Discuss code, ask questions & collaborate with the developer community.
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