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Super Study Guide: Transformers y Grandes Modelos de Lenguaje
Este libro es una guía concisa e ilustrada para cualquiera que desee comprender el funcionamiento interno de los Grandes Modelos de Lenguaje, ya sea de cara a realizar entrevistas, proyectos o para satisfacer su curiosidad.
This book is a translation into Spanish of Super Study Guide: Transformers & Large Language Models which was originally written in English
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About
About the Book
Este libro es una guía concisa e ilustrada para cualquiera que desee comprender el funcionamiento interno de los Grandes Modelos de Lenguaje, ya sea de cara a realizar entrevistas, proyectos o para satisfacer su curiosidad.
Está dividido en 5 partes:
- Fundamentos: Introducción a las redes neuronales y a los conceptos importantes de aprendizaje profundo para entrenamiento, evaluación y prueba.
- Embeddings: Algoritmos de tokenización, embeddings de palabras (word2vec) y embeddings de oraciones (RNN, LSTM, GRU).
- Transformers: Motivación detrás de su mecanismo de autoatención, visión detallada de la arquitectura codificador-decodificador y modelos clave relacionados como BERT, GPT y T5.
- Grandes Modelos de Lenguaje: Modelos basados en Transformers que logran un rendimiento más avanzado con consejos sobre ingeniería de prompts, junto con cómo hacer ajustes finos (SFT, PEFT) y ajuste por preferencias (RLHF, DPO).
- Aplicaciones: Extracción de sentimientos, traducción automática, elaboración de resúmenes, generación aumentada por recuperación y muchas más.
This book is a translation into Spanish of Super Study Guide: Transformers & Large Language Models which was originally written in English
Author
About the Authors
Afshine Amidi
Afshine Amidi is an Adjunct Professor at Stanford University, where he teaches two AI courses: "CME 295 - Transformers & Large Language Models" and "CME 296 - Diffusion & Large Vision Models". In addition to his academic work, he currently leads LLM efforts for promotional writing at Netflix. Previously, he worked at Uber and at Google on the Gemini team. He holds a Bachelor’s and a Master’s Degree from École Centrale Paris and a Master’s Degree from MIT.
Shervine Amidi
Shervine Amidi is an Adjunct Professor at Stanford University where he teaches two AI courses: "CME 295 - Transformers & Large Language Models" and "CME 296 - Diffusion & Large Vision Models". In addition to his academic work, he currently leads LLM efforts for enterprise productivity at Netflix. Previously, he worked at Uber and at Google on the Gemini team. He holds a Bachelor’s and a Master’s Degree from École Centrale Paris and a Master’s Degree from Stanford University.
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