model-certification

Certify a HuggingFace model by running an end-to-end pipeline that includes playbook creation, tiered qualification runs, evidence collection, and MQS scoring to validate reliability before deployment.

Model certification is the process of qualifying a model's performance and safety using property-based testing and evidence collection. You need it to ensure reliability before deploying a new LLM to production.

Yes, you can run tiered qualification tests including Smoke, MVP, Quick, Standard, and Deep tiers to match your specific validation needs and time constraints during model certification.

Property-based testing in model certification applies Popperian falsification methodology to challenge model stability and quality, enforcing SafeTensors ground truth and LAYOUT-002 compliance for robust validation.

The best way to generate evidence and update a registry is through an automated certification pipeline that executes qualification runs, calculates MQS scoring, and automatically updates the model's status in the registry.

Yes, HuggingFace model certification enforces SafeTensors ground truth and LAYOUT-002 compliance as core validation constraints throughout the qualification and evidence collection process.