9 integrations
Training integrations
Train on your Roboflow datasets in the notebook or framework you prefer.
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AWS Rekognition Custom LabelsLabel and version a dataset in Roboflow, then send it to Amazon S3 as a SageMaker Ground Truth manifest that Rekognition Custom Labels can train on.
Amazon SageMakerPull Roboflow dataset versions into SageMaker notebooks with the Python package, train there, then upload the weights to Roboflow or serve the model on a SageMaker endpoint.
Amazon SageMaker Studio LabsRoboflow has produced notebooks showing how to train computer vision models that work in Amazon SageMaker Studio Lab.
Azure Custom VisionExport a Roboflow dataset version straight into an Azure Custom Vision project and train it there. Enterprise plans only; Microsoft retires Custom Vision in 2028.
Create MLExport a Roboflow dataset as CreateML JSON and train an object detector in Apple's Create ML app on your Mac, for Core ML models that run on iPhone and iPad.
Google ColabTrain RF-DETR, YOLO26, YOLO11 and other models on your Roboflow datasets in our Colab notebooks, then upload the weights to Roboflow to deploy them.
Hugging FaceImport Hugging Face Hub datasets into Roboflow, and load RF-DETR models, including ones you train on Roboflow, with the Hugging Face Transformers library.
YOLOv5Export Roboflow datasets in YOLOv5 PyTorch TXT, train YOLOv5 in our notebooks, then upload the weights to serve the model from Roboflow's API or your own hardware.
YOLOv8Export Roboflow datasets for YOLOv8, train detection, segmentation or keypoint models with Ultralytics, then upload the weights to run them on Roboflow.
Don’t see your tool?
Roboflow imports and exports the common annotation formats and has a REST API and Python SDK, so most stacks connect without a dedicated integration.