| Like question answering, there are two types of summarization: | |
| extractive: identify and extract the most important sentences from the original text | |
| abstractive: generate the target summary (which may include new words not in the input document) from the original text; the [SummarizationPipeline] uses the abstractive approach | |
| from transformers import pipeline | |
| summarizer = pipeline(task="summarization") | |
| summarizer( | |
| "In this work, we presented the Transformer, the first sequence transduction model based entirely on attention, replacing the recurrent layers most commonly used in encoder-decoder architectures with multi-headed self-attention. |