Vector Hyperbolic Embed hierarchical data in the Poincare ball model using . When to use Use this skill when your data has inherent hierarchy — dependency trees, module structures, taxonomies, org charts, ontologies. Hyperbolic space captures hierarchical distances with far fewer dimensions than Euclidean embeddings. Steps 1. Ensure [email protected] is available : 2. Generate a base ONNX embedding ([email protected] does not expose a flag on ): 3. Project into the Poincare ball in your own code (or via the experimental neural substrate): For an ad-hoc projection, normalize the 384-dim vector to…