September 2024
Intermediate to advanced
408 pages
12h 11m
Spanish
book
Procesamiento del Lenguaje Natural con Transformadores, Edición Revisada
by Lewis Tunstall, Leandro von Werra, Thomas Wolf
Content preview from Procesamiento del Lenguaje Natural con Transformadores, Edición Revisada
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Capítulo 6. Resumir
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En un momento u otro, probablemente hayas necesitado resumir un documento, ya sea un artículo de investigación, un informe de resultados financieros o un hilo de correos electrónicos. Si lo piensas, esto requiere una serie de habilidades, como comprender pasajes largos, razonar sobre el contenido y producir un texto fluido que incorpore los temas principales del documento original. Además, resumir con precisión un artículo de noticias es muy diferente de resumir un contrato legal, por lo que ser capaz de hacerlo requiere un sofisticado grado de generalización del dominio. Por estas razones, el resumen de texto es una tarea difícil para los modelos neurales del lenguaje, incluidos los transformadores. A pesar de estos retos, el resumen de texto ofrece la posibilidad de que los expertos del dominio aceleren significativamente sus flujos de trabajo, y las empresas lo utilizan para condensar el conocimiento interno, resumir contratos, generar automáticamente contenido para comunicados en medios sociales, etc.
Para ayudarte a comprender los retos que esto implica, este capítulo explorará cómo podemos aprovechar los transformadores preentrenados para resumir documentos. El resumen es una tarea clásica de secuencia a secuencia (seq2seq) con un texto de entrada y un texto de destino. Como vimos en elCapítulo 1, aquí es donde destacan los transformadores ...
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