Skills

Codonfm Setup

Set up the public CodonFM v1 repository and download public Encodon checkpoints.

Install

npx skills add NVIDIA/skills --skill codonfm-setup -g -a claude-code -y
Repository
NVIDIA/skills3.8k
Category
Engineering
Updated
5d ago
License
Apache-2.0
Context cost
Mediumabout 3,000 tokens
Runs scripts
No, instructions only

What it does

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.

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 MODEL_ARCHITECTURES 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 scopeAction and completion condition
Instructions onlyInspect the supplied source/configuration, provide the commands described under Reporting setup instructions, then stop. No installation or GPU verification is required.
Checkpoint onlyFollow Download a checkpoint, check the downloaded files, report their paths, then stop. No Docker, GPU, or model runtime is required.
Working model environmentFollow Runtime preflight, choose the container or direct-host path, then Verify the runtime. Report the checks performed and any remaining limitations.
Read the whole SKILL.md on GitHub

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