| March 19, 2026 15:12 UTC | May 6, 2026 09:24 UTC | ||||
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| 38 | "Organization" refers to a workspace representing a legal entity and/or several | 38 | "Organization" refers to a workspace representing a legal entity and/or several | ||
| > | Users. A User can be part of multiple organizations. | > | Users. A User can be part of multiple organizations. | ||
| 39 | "Premium Support" refers to qualified information or any other materials provide | 39 | "Premium Support" refers to qualified information or any other materials provide | ||
| > | d by Hugging Face via email or any other instant messaging or communication serv | > | d by Hugging Face via email or any other instant messaging or communication serv | ||
| > | ice to the Customer to address the Customer’s questions on the use and optimizat | > | ice to the Customer to address the Customer’s questions on the use and optimizat | ||
| > | ion of the Hugging Face Open-Source Libraries, Hugging Face or Customer Models. | > | ion of the Hugging Face Open-Source Libraries, Hugging Face or Customer Models. | ||
| 40 | "Repository" refers to a data structure which contains all of the project files | 40 | "Repository" refers to a data structure which contains all of the project files | ||
| > | and the entire revision history. A Repository may be public (i.e. anyone on the | > | and the entire revision history. A Repository may be public (i.e. anyone on the | ||
| > | internet can see it, but only you or members of your organization can make chang | > | internet can see it, but only you or members of your organization can make chang | ||
| > | es) or private (i.e. only you or members of your organization can see and make c | > | es) or private (i.e. only you or members of your organization can see and make c | ||
| > | hanges to the repository). | > | hanges to the repository). | ||
| n | 41 | "Services" refer to the products and/or services we offer or provide, and that y | n | 41 | "Services" refer to the products and/or services we offer or provide, and that y |
| > | ou access, use or purchase. Services may include limited licenses or subscriptio | > | ou access, use or purchase. Services may include limited licenses or subscriptio | ||
| > | ns to access or use certain offerings in accordance with these Terms, including | > | ns to access or use certain offerings in accordance with these Terms, including | ||
| > | use of Models, Datasets, Hugging Face Open-Sources Libraries, the Inference Prov | > | use of Models, Datasets, Hugging Face Open-Sources Libraries, the Inference Prov | ||
| > | iders, AutoTrain, Expert Support, Infinity or other Content. Reference to "purch | > | iders, AutoTrain, Enterprise Support, Infinity or other Content. Reference to "p | ||
| > | ases" and/or "sales" mean a limited right to access and use a Service (not a tra | > | urchases" and/or "sales" mean a limited right to access and use a Service (not a | ||
| > | nsfer or any ownership right, title, or interest) in accordance with these Terms | > | transfer or any ownership right, title, or interest) in accordance with these T | ||
| > | . | > | erms. | ||
| 42 | "User" refers to the individual person, company or organization that accesses, r | 42 | "User" refers to the individual person, company or organization that accesses, r | ||
| > | eceives, or uses the Services. That's you! | > | eceives, or uses the Services. That's you! | ||
| 43 | 👩💻 Your Use of the Services | 43 | 👩💻 Your Use of the Services | ||
| 44 | Here are the Services we offer, and how you should use them. | 44 | Here are the Services we offer, and how you should use them. | ||
| 48 | Hugging Face private Hub: where you can build, benchmark, share, version and dep | 48 | Hugging Face private Hub: where you can build, benchmark, share, version and dep | ||
| > | loy Models, Datasets and Machine Learning Applications, that are only accessible | > | loy Models, Datasets and Machine Learning Applications, that are only accessible | ||
| > | by You or your Organization(s) | > | by You or your Organization(s) | ||
| 49 | Inference Providers Service: where you or your organization(s) can run inference | 49 | Inference Providers Service: where you or your organization(s) can run inference | ||
| > | via application programming interface on machine learning models publicly or pr | > | via application programming interface on machine learning models publicly or pr | ||
| > | ivately hosted on our Model Hub | > | ivately hosted on our Model Hub | ||
| 50 | AutoTrain premium Service: create state of the art Models from your own training | 50 | AutoTrain premium Service: create state of the art Models from your own training | ||
| > | data, everything being automatically hosted privately on the Model Hub. You can | > | data, everything being automatically hosted privately on the Model Hub. You can | ||
| > | then share them publicly and/or serve them through the Inference Providers Serv | > | then share them publicly and/or serve them through the Inference Providers Serv | ||
| > | ice for example. | > | ice for example. | ||
| t | 51 | Expert Support: get Premium Support on the use of our open source and all our se | t | 51 | Enterprise Support: get Premium Support on the use of our open source and all ou |
| > | rvices and/or products. | > | r services and/or products. | ||
| 52 | Infinity Service: deploy end-to-end optimized inference pipelines for state of t | 52 | Infinity Service: deploy end-to-end optimized inference pipelines for state of t | ||
| > | he art Transformers Models. | > | he art Transformers Models. | ||
| 53 | Hardware Partner Program: access State of the Art hardware and hardware-specific | 53 | Hardware Partner Program: access State of the Art hardware and hardware-specific | ||
| > | machine learning optimization techniques for production performance. | > | machine learning optimization techniques for production performance. | ||
| 54 | Inference Endpoints: easily deploy machine learning models on dedicated, secure | 54 | Inference Endpoints: easily deploy machine learning models on dedicated, secure | ||
| > | and autoscaling infrastructure | > | and autoscaling infrastructure | ||
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