Update documentation on seq2seq models with absolute positional embeddings, to be in line with Tips section for BERT and GPT2 (#20068)

Co-authored-by: jordiclive <jordiclive19@imperial.ac.uk>

docs/source/en/model_doc/bart.mdx

@@ -32,6 +32,11 @@ According to the abstract,
   state-of-the-art results on a range of abstractive dialogue, question answering, and summarization tasks, with gains
   of up to 6 ROUGE.
 
+Tips:
+
+- BART is a model with absolute position embeddings so it's usually advised to pad the inputs on the right rather than
+  the left.
+
 This model was contributed by [sshleifer](https://huggingface.co/sshleifer). The Authors' code can be found [here](https://github.com/pytorch/fairseq/tree/master/examples/bart).