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ON THIS PAGE

  • Overview
  • Model File(s) Preparation
  • Supported PyTorch YOLO Models
  • Model Card Preparation

Model Preparation

Overview

Before uploading a custom model to the Model Registry, you need to prepare two components: the Model File(s) and an accompanying Model Card. This section walks you through how to prepare them properly.

Model File(s) Preparation

  • Train a model of choice or obtain an existing model of interest.
  • If the model is in ONNX (.onnx), OpenVINO IR (.xml and .bin), or TensorFlow Lite (.tflite) format, you can skip this step. If the model is one of the supported PyTorch YOLO models, you can also skip this step. Else convert it to one of the formats mentioned above. For more information, see the guidelines in the Model Source Preparation section on the Model Conversion page.
  • For custom models, package the model file(s) into an ONNX NN Archive before uploading them to Hub. This is the recommended starting point because it stores the source model's tensor metadata, preprocessing, and optional output metadata together with the model and lets Hub reuse that information during conversion.

Supported PyTorch YOLO Models

Hub supports a defined subset of PyTorch YOLO models for direct upload and conversion. The currently supported families include YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLO11, YOLO12, YOLO26, YOLOE, and Gold-YOLO. For the exact set of supported YOLO families, variants, and current limitations, refer to the upstream supported models table.

Model Card Preparation

Model card can be abribtrary for private (team-owned) models. For public models, however, it should follow the structure and contain the information described in the Model Card section on the main page. It's adviced to consult the model release paper, GitHub repositories, and other relevant resources to obtain the required information. To get a better idea of the Model Card structure and what information should be included, we suggest checking our Model Card Template or looking at the Model Cards of existing entries in Hub.