The outcome
Share a resource that others can evaluate and use without hidden training claims, ambiguous rights, or missing technical requirements.
Step by step
A workflow you can repeat.
- 01
Document training-data rights and consent, model purpose, base model, method, known limitations, prohibited uses, and the license you can grant.
- 02
Remove secrets and personal data, scan the artifact, calculate hashes, and test the release in a clean environment with exact dependencies.
- 03
Create representative samples with reproducible prompts and settings, label material AI content, and avoid deceptive or unauthorized likeness examples.
- 04
Publish the correct model type and version with files, trained words, compatibility, permissions, safety notes, and clear commercial conditions.
- 05
Monitor reports and failures, keep immutable version notes and hashes, correct claims transparently, and remove or supersede unsafe releases promptly.
Working standard
What good use looks like.
- Publish honest provenance and limitations.
- Test from a clean environment.
- Keep version notes and hashes immutable.
Official references