Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.
WHAT YOU BECOME
Perfect for these scenarios
Quickly identify and fix syntax errors in broken YAML files
Ensure pipeline configurations parse correctly before deployment
Verify how your tools handle malformed YAML edge cases
Prevent issues from unparsable configs breaking your systems
MEASURED GAIN
Proven benefits and measurable impact
Reduce time spent identifying YAML syntax issues significantly
Cut deployment errors caused by invalid YAML configs in half
Complete confidence your YAML files will always load
WHAT YOU GET
Files, tags and the three-step install
Tip: Read the documentation and the code before first use, so you know what it does and which permissions it needs.
NEXT SCRIPTS
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