Agent skill · nvidia
codonfm-setup
Set up the public CodonFM v1 repository and download public Encodon checkpoints. Use for requests to build or launch the CodonFM development container, configure local data/checkpoint mounts, verify GPU access, or download public Encodon 80M, 600M, 1B, or Cdwt-1B weights. Do not use for Decodon, Encodon 5B/10B, missense-aggregation, or codon-optimization setup because those implementations are not in the public repository.
What it needs
About 7k tokens when loaded.
What this skill does
CodonFM public setup Operate from the public CodonFM repository root. Support only the checked-in public v1 code and public Encodon checkpoints. Instructions 1. Determine whether the user wants instructions, a downloaded checkpoint, a working model environment, or a combination of these. 2. For setup instructions or runtime work, inspect the supplied files and configuration directly: the runner, model configuration, Dockerfile, launcher, and requirements. Runtime setup requires a checkout; a supplied source archive is sufficient for preparing instructions. 3. Check the public-v1 boundaries. For an unsupported request, inspect MODELARCHITECTURES in src/config.py, the model modules, and any requested script before explaining the boundary and ending that path. Runner argument choices alone do not establish implementation support. 4. Reuse available environments and checkpoints, and choose explicit paths from the user's project. 5. Follow only the requested paths below. Environment setup alone does not require a checkpoint download; download weights only when the request needs them and a suitable local checkpoint is unavailable. Requested scope Action and completion condition --- --- Instructions only Inspect the supplied source/configuration, provide the commands described under Reporting setup instructions, then stop. No installation or GPU verification is required. Checkpoint only Follow Download a checkpoint, check the downloaded files, report their paths, then stop. No Docker, GPU, or model runtime is required. Working model environment Follow Runtime preflight, choose the container or direct-host path, then Verify the runtime. Report the checks performed and any remaining limitations. For supplied source archives, inspect selected files with the available Python 3 standard library (zipfile.ZipFile.namelist() and read()) without extracting the whole archive. If extraction is needed, use a fresh directory from mktemp -d or tempfile.mkdtemp(). …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/bionemo-codonfm-setup