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Amidi A. Super Study Guide. Transformers & Large Language Models 2024

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Amidi A. Super Study Guide. Transformers & Large Language Models 2024

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Category: Other
Total size: 9.18 MB
Added: 2025-03-10 23:39:04

Share ratio: 12 seeders, 2 leechers
Info Hash: 0515A05E4B3AAAA6A7D394522723AC8FE42041CC
Last updated: 15.1 hours ago

Description:

Textbook in PDF format This book is a concise and illustrated guide for anyone who wants to understand the inner workings of large language models in the context of interviews, projects or to satisfy their own curiosity. It is divided into 5 parts: Foundations: primer on neural networks and important deep learning concepts for training and evaluation Embeddings: tokenization algorithms, word-embeddings (word2vec) and sentence embeddings (RNN, LSTM, GRU) Transformers: motivation behind its self-attention mechanism, detailed overview on the encoder-decoder architecture and related variations such as BERT, GPT and T5, along with tips and tricks on how to speed up computations Large language models: main techniques to tune Transformer-based models, such as prompt engineering, (parameter efficient) finetuning and preference tuning Applications: most common problems including sentiment extraction, machine translation, retrieval-augmented generation and many more