What requirement must be met for the ML model used in pre-labeling to work?

For the ML model used in pre-labeling to function properly, it must be publicly available via a URL. This requirement ensures that the model can be easily accessed and utilized for the pre-labeling process. When the ML model is accessible online, it can be integrated seamlessly into the workflow, allowing for efficient and effective pre-labeling of data.

Having the model publicly available not only facilitates access for immediate use but also ensures that it can be regularly updated or maintained by the provider. This is critical, as pre-labeling relies on up-to-date models to generate accurate labels for data, particularly in dynamic industries where data evolves rapidly.

The other options typically do not align with the requirements for pre-labeling. A proprietary model may provide benefits regarding exclusivity or optimization for specific tasks, but it wouldn't necessarily meet the accessibility needs in the same way. Local storage options offer flexibility, yet may limit ease of access which is crucial for real-time operations. As for supporting multiple languages, while it can be a valuable aspect for broader usability, it is not a fundamental requirement for the model to function in pre-labeling specifically.