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Transformers for Natural Language Processing Build Innovative Deep Neural Network Architectures for NLP with Python, Pytorch, TensorFlow, BERT, RoBERTa, and More.

Being the first book in the market to dive deep into the Transformers, it is a step-by-step guide for data and AI practitioners to help enhance the performance of language understanding and gain expertise with hands-on implementation of transformers using PyTorch, TensorFlow, Hugging Face, Trax, and...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Rothman, Denis
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, Limited, 2021.
Temas:
Acceso en línea:Texto completo
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Tabla de Contenidos:
  • Table of Contents Getting Started with the Model Architecture of the Transformer Fine-Tuning BERT Models Pretraining a RoBERTa Model from Scratch Downstream NLP Tasks with Transformers Machine Translation with the Transformer Text Generation with OpenAI GPT-2 and GPT-3 Models Applying Transformers to Legal and Financial Documents for AI Text Summarization Matching Tokenizers and Datasets Semantic Role Labeling with BERT-Based Transformers Let Your Data Do the Talking: Story, Questions, and Answers Detecting Customer Emotions to Make Predictions Analyzing Fake News with Transformers Appendix: Answers to the Questions.