Torch Geometric
If you're building graph neural networks with PyTorch, this gets you up and running with PyTorch Geometric fast. It covers the core use cases: node and graph classification, link prediction, molecular property prediction for drug discovery, and handling 3D geometric data like point clouds. The skill includes patterns for mini-batch processing and multi-GPU training, which matters when you're working with large graphs. With 27.7K stars on GitHub and 285 installs, it's a solid resource for anyone doing deep learning on irregular structures. Most useful when you need to move beyond standard tensor operations into graph-structured data, whether that's citation networks, social graphs, or chemical structures.
- skills.sh installs
- 294
- GitHub stars
- 30.2K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add davila7/claude-code-templates --skill torch-geometric --agent claude-codeInstalls into .claude/skills of the current project.
Files
If you're building graph neural networks with PyTorch, this gets you up and running with PyTorch Geometric fast. It covers the core use cases: node and graph classification, link prediction, molecular property prediction for drug discovery, and handling 3D geometric data like point clouds. The skill includes patterns for mini-batch processing and multi-GPU training, which matters when you're working with large graphs. With 27.7K stars on GitHub and 285 installs, it's a solid resource for anyone doing deep learning on irregular structures. Most useful when you need to move beyond standard tensor operations into graph-structured data, whether that's citation networks, social graphs, or chemical structures.
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- Repository
- github.com/davila7/claude-code-templates
- First seen
- Jun 3, 2026
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