L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

inference-cli

inference-cli

Run OmegaFold CLI inference from FASTA to PDB safely, including devices, weights, resources, dry-run validation, and troubleshooting.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: inference-cli description: "Run OmegaFold CLI inference from FASTA to PDB safely, including devices, weights, resources, dry-run validation, and troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

OmegaFold inference CLI

Use this sub-skill when a task needs to run or validate OmegaFold command-line inference from a FASTA file to PDB outputs. Prefer the installed omegafold console script; use the installed-package fallback python -m omegafold only when the console script is unavailable but the package import works.

Fast path

  1. Validate the CLI without downloading model weights:
    python scripts/omegafold_cli_smoke.py
    
  2. Inspect a FASTA and print a planned command without running inference:
    python scripts/omegafold_cli_smoke.py --fasta INPUT_FILE.fasta --output-dir OUTPUT_DIRECTORY --model 2 --device cuda
    
  3. Run full inference only when weights, device, memory, and runtime are acceptable:
    omegafold INPUT_FILE.fasta OUTPUT_DIRECTORY --model 1 --device cuda
    

Route by need

  • Use CLI reference for flags, defaults, model choices, command templates, and installed-module fallback syntax.
  • Use inference workflow for safe validation, weights/cache decisions, device/resource planning, and output expectations.
  • Use troubleshooting for install/import errors, Python and Torch compatibility, missing weights, device mismatch, OOM, and output mistakes.
  • Use scripts/omegafold_cli_smoke.py for no-download CLI help checks and FASTA dry-run planning.
  • For FASTA normalization details, output file naming, PDB confidence fields, and validation of generated structures, route to data-and-outputs.
  • For direct Python use of OmegaFold, make_config, fasta2inputs, and tensor contracts, route to model-api.

Safety defaults

  • omegafold --help is safe: it prints parser help and does not load weights.
  • omegafold INPUT_FILE.fasta OUTPUT_DIRECTORY ... is not a smoke test: argument parsing selects a model, may download weights, then loads a large torch checkpoint before inference.
  • Avoid full inference unless the user has approved network/download cost or has provided a local --weights_file, and the selected --device has enough memory.
Skills enregistrées