Extract per-molecule embeddings from any encoder-bearing KERMT checkpoint (grover_base / cmim / hybrid / finetuned). Writes one .npy per readout type (atom_from_atom, bond_from_atom, atom_from_bond, bond_from_bond) plus canonical_smiles.npy and validity.npy. Calls task/extract_embeddings.py (which featurizes SMILES on the fly — no pre-computed features needed).
How to install kermt-embed?
nvidia-bionemo/bionemo-agent-toolkit/kermt-embed
$npx -y skills add nvidia-bionemo/bionemo-agent-toolkit --skill kermt-embedInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/nvidia-bionemo/bionemo-agent-toolkit" --skill "nvidia-bionemo/bionemo-agent-toolkit/kermt-embed"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/nvidia-bionemo/bionemo-agent-toolkit" that are relevant to the current task. Run `npx skills add "https://github.com/nvidia-bionemo/bionemo-agent-toolkit"` and select the relevant skills, then follow their instructions.
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