Model publishers are encouraged to state explicitly what their model is designed to do and what uses they consider inappropriate or outside the model's intended purpose.
This analysis describes what Hugging Face's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
Intended use declarations define the scope of responsible use as understood by the model publisher, and out-of-scope use declarations may be relevant to liability allocation if a model is deployed in a context the publisher explicitly identified as inappropriate.
Interpretive note: The document describes intended use documentation as a recommendation rather than a mandatory requirement, so the presence and completeness of this information varies by model publisher.
The intended use section of a model card tells users what the publisher designed the model for, while the out-of-scope section identifies uses the publisher has explicitly flagged as problematic, which users and organizations should review before integrating any model.
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"Model cards should include information about the intended uses of the model and the uses that are out of scope for the model. This information helps users understand how the model is intended to be used and what uses are not appropriate.— Excerpt from Hugging Face's Hugging Face Model Card Guidelines
(1) REGULATORY LANDSCAPE: Intended use declarations engage the EU AI Act's risk classification framework, which assigns compliance obligations based on the context in which an AI system is deployed. The FTC's guidance on AI and non-deceptive practices is relevant where a model is deployed in a context materially different from its stated intended use. (2) GOVERNANCE EXPOSURE: Medium. Organizations deploying models in contexts identified as out-of-scope by the publisher may face increased liability exposure, as the out-of-scope declaration could be used as evidence of known risk in litigation or regulatory proceedings. (3) JURISDICTION FLAGS: EU organizations must assess intended use declarations against the EU AI Act's prohibited and high-risk use category definitions. US organizations in financial services, healthcare, and employment sectors should evaluate intended use against sector-specific AI governance guidance from relevant regulators. (4) CONTRACT AND VENDOR IMPLICATIONS: Procurement teams should treat out-of-scope use declarations as material contract review triggers and confirm that their intended deployment does not fall within categories the model publisher has explicitly flagged. Vendor agreements should address liability allocation for deployments that deviate from stated intended use. (5) COMPLIANCE CONSIDERATIONS: Compliance teams should document their assessment of whether their deployment context aligns with the model card's stated intended use, and maintain records of this assessment as part of their AI governance documentation.
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Intended use declarations define the scope of responsible use as understood by the model publisher, and out-of-scope use declarations may be relevant to liability allocation if a model is deployed in a context the publisher explicitly identified as inappropriate.
The intended use section of a model card tells users what the publisher designed the model for, while the out-of-scope section identifies uses the publisher has explicitly flagged as problematic, which users and organizations should review before integrating any model.
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