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Master thesis with code investigating methods for incorporating long-context reasoning in low-resource languages, without the need to pre-train from scratch. We investigated if multilingual models could inherit these properties by making it an Efficient Transformer (s.a. the Longformer architecture).
LongPegasus package is used for inducing longformer self attention over base pegasus abstractive summarization model to increase the token limit and performance.