Reword E2E training and inference tips in the vision guides (#5217)

* chore: reword e2e workflow suggestions for image guides.

Co-authored-by: Steven Liu <[email protected]>

* Apply suggestions from code review

Co-authored-by: Steven Liu <[email protected]>

Co-authored-by: Steven Liu <[email protected]>

Author: sayakpaul

docs/source/image_classification.mdx

@@ -82,7 +82,8 @@ You can verify the transformation worked by indexing into the `pixel_values` of
 
 <Tip>
 
-To learn how to leverage 🤗 Datasets end-to-end for training an image classification model, refer to
-[this notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb).
+Now that you know how to process a dataset for image classification, learn
+[how to train an image classification model](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb)
+and use it for inference.
 
 </Tip>

docs/source/object_detection.mdx

@@ -154,9 +154,14 @@ You can verify the transform works by visualizing the 10th example:
 ... )
 ```
 
-To learn how to leverage parts of 🤗 datasets end-to-end for training an object detection model, refer to
-[this notebook](https://nbviewer.org/github/NielsRogge/Transformers-Tutorials/blob/master/YOLOS/Fine_tuning_YOLOS_for_object_detection_on_custom_dataset_%28balloon%29.ipynb).
-
 <div class="flex justify-center">
     <img src="https://huggingface.co/datasets/nateraw/documentation-images/resolve/main/visualize_detection_example_transformed_2.png">
 </div>
+
+<Tip>
+
+Now that you know how to process a dataset for object detection, learn
+[how to train an object detection model](https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/YOLOS/Fine_tuning_YOLOS_for_object_detection_on_custom_dataset_(balloon).ipynb)
+and use it for inference.
+
+</Tip>

docs/source/semantic_segmentation.mdx

@@ -168,6 +168,10 @@ In this guide, you have used `albumentations` for augmenting the dataset. It's a
     <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/datasets/torchvision_seg.png">
 </div>
 
+<Tip>
+
 Now that you know how to process a dataset for semantic segmentation, learn
 [how to train a semantic segmentation model](https://huggingface.co/docs/transformers/tasks/semantic_segmentation)
-and use it for inference.
+and use it for inference.
+
+</Tip>