Add link to notebooks (#15791)

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

docs/source/model_doc/vilt.mdx

@@ -32,6 +32,8 @@ times faster than previous VLP models, yet with competitive or better downstream
 
 Tips:
 
+- The quickest way to get started with ViLT is by checking the [example notebooks](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/ViLT)
+  (which showcase both inference and fine-tuning on custom data).
 - ViLT is a model that takes both `pixel_values` and `input_ids` as input. One can use [`ViltProcessor`] to prepare data for the model.
   This processor wraps a feature extractor (for the image modality) and a tokenizer (for the language modality) into one.
 - ViLT is trained with images of various sizes: the authors resize the shorter edge of input images to 384 and limit the longer edge to