Update how-to-inference-onnx-automl-image-models.md

Author: ssalgadodev

articles/machine-learning/how-to-inference-onnx-automl-image-models.md

@@ -333,7 +333,7 @@ Every ONNX model has a predefined set of input and output formats.
 
 # [Multi-class image classification](#tab/multi-class)
 
-This example applies the model trained on the [fridgeObjects](https://cvbp-secondary.z19.web.core.windows.net/datasets/image_classification/fridgeObjects.zip) dataset with 134 images and 4 classes/labels to explain ONNX model inference. For more information on training an image classification task, see the [multi-class image classification notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items).
+This example applies the model trained on the [fridgeObjects](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) dataset with 134 images and 4 classes/labels to explain ONNX model inference. For more information on training an image classification task, see the [multi-class image classification notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items).
 
 ### Input format