In the original paper Section 6:

We used sinusoidal positional encoding

and Section 6.2:

This would present a problem for position embeddings which would never be updated for longer input lengths, but we confirm the postulation that sinusoidal positional encodings (Vaswani et al., 2017) generalize well when fine-tuning PEGASUSLARGE beyond the input lengths observed in training up to Linput = 1024 tokens.

So you can use longer input than training, but you have to observe if model still generalize with longer input.