An administrator attempts to import a pre-trained model into Nutanix Enterprise AI (NAI), but the...

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When a model import completes but the model is not listed as available for deployment, the issue is almost always related tocompatibility or metadata validation.

Validation Check:NAI requires specific file formats (e.g., safetensors, pytorch_model.bin) and a valid configuration file (config.json) to recognize and serve a model. If the imported repository lacks these files, uses an unsupported architecture, or has a corrupted metadata file, the platform cannot register it as a valid "deployable" entity.

Action:The administrator must verify the source repository to ensure themodel format and metadataalign with NAI's supported standards (e.g., checking for the correct task type like "text-generation" in the config).

Other Options:

Public IPs (B) are network configurations unrelated to the internal model registry list.

API Keys (C) are for client-side access, not model management visibility.

Restarting the cluster (D) is a disruptive step that does not address the underlying data validation error.