Individual skill
kermt-embed
Extract per-molecule embeddings from any encoder-bearing KERMT checkpoint. Use a local checkpoint or optionally download a pinned Hugging Face model bundle using HF_TOKEN if configured. Run containerized embedding extraction and write model bundles, per-readout .npy embeddings, canonical SMILES, and validity arrays to user-selected host directories.
skills/bionemo-kermt-embed/SKILL.md
Source commit 25340619336e89bcc40365c28bfe9e790430468e
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 2, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 3,895
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- agentic-ai Repository topic
- ai-agents Repository topic
- claude-code Repository topic
- codex Repository topic
- coding-agents Repository topic
- cuda Repository topic
- developer-tools Repository topic
- llm Repository topic
- omniverse Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
BENCHMARK.mddoc · 7,783 bytesSKILL.mdcore · 7,694 bytesSKILL.mdcore · 7,694 bytesSKILL.mdcore · 7,694 bytesSKILL.mdcore · 7,694 bytesSKILL.mdcore · 7,694 bytesSKILL.mdcore · 7,694 bytesSKILL.mdcore · 7,694 bytesSKILL.mdcore · 7,694 bytesconfig/defaults_embed.jsonasset · 718 bytesconfig/released_model.jsonasset · 398 bytesevals/evals.jsonasset · 7,002 bytesreferences/released-models.mddoc · 1,634 bytesscripts/_utils.pyruns · 14,483 bytesscripts/check_checkpoint.pyruns · 20,605 bytesscripts/check_data.pyruns · 12,185 bytesscripts/fetch_released_model.pyruns · 8,108 bytesscripts/kermt_container.shruns · 19,370 bytesscripts/prepare_data.pyruns · 37,383 bytesscripts/run_extract_embeddings.pyruns · 8,967 bytesskill-card.mddoc · 4,343 bytesskill.oms.sigasset · 6,969 bytes
Read excerpt
# kermt-embed
Extract per-molecule embeddings from any encoder-bearing KERMT checkpoint.
The skill is the workflow orchestrator: validate ckpt, validate CSV, clean
SMILES, launch the runner blocking, return the per-readout `.npy` files.
## Skill and runtime paths
Set `SKILL_DIR` to the absolute path of this installed skill directory. Export
`KERMT_REPO` as the absolute path to the KERMT checkout used for model
execution. The bundled container helper mounts that checkout at
`/workspace` and this skill at `/skill` (read-only). Commands inside
the container use `/skill/scripts/`; defaults are bundled in `config/`.
See [Released models](references/released-models.md) for checkpoint bundle requirements.