March 2025
Intermediate to advanced
366 pages
10h 23m
Portuguese (Portugal, Brazil)
Content preview from Concebe grandes aplicações de modelos de linguagem
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Capítulo 11. Aprendizagem de Representações e Embeddings
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No capítulo anterior, aprendemos como podemos fazer a interface dos modelos de linguagem com ferramentas externas, incluindo armazenamentos de dados. Os dados externos podem estar presentes sob a forma de ficheiros de texto, tabelas de bases de dados e gráficos de conhecimento. Os dados podem abranger uma grande variedade de tipos de conteúdo, desde bases de conhecimento próprias de um domínio específico até resultados intermédios e outputs gerados por LLMs.
Se os dados forem estruturados, por exemplo, se residirem numa base de dados relacional, o modelo de linguagem pode emitir uma consulta SQL para recuperar os dados de que necessita. Mas e se os dados estiverem presentes de forma não estruturada?
Uma forma de obter dados de conjuntos de dados de texto não estruturados é pesquisar por palavras-chave ou utilizar expressões regulares. Para o exemplo do CFO da Apple no capítulo anterior, podemos obter texto que contenha menções ao CFO a partir de um corpus que contenha divulgações financeiras, na esperança de que contenha a data de adesão ou informações sobre o mandato. Por exemplo, podes usar a regex:
pattern=r"(?i)\b(?:C\.?F\.?O|Chief\s+Financial\s+Officer)\b"
A pesquisa por palavras-chave é limitada na sua eficácia. Há um grande número de formas de exprimir a data de entrada ou o cargo de diretor financeiro ...
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