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Mastering NLP from Foundations to LLMs

Mastering NLP from Foundations to LLMs

By : Gazit, Meysam Ghaffari
4.9 (24)
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Mastering NLP from Foundations to LLMs

Mastering NLP from Foundations to LLMs

4.9 (24)
By: Gazit, Meysam Ghaffari

Overview of this book

Do you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.
Table of Contents (14 chapters)
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Employing LLMs from Hugging Face via Python

Now, we will review a code notebook that exemplifies implementing an open source LLM locally using Hugging Face’s free resources. We will continue with the same notebook from the previous section, Setting Up Close Source and Open Source LLMs:

  1. Install the required Python libraries: To freely work with Hugging Face’s open source models and other various resources, we need to install the necessary Python library.

    Via pip on the Terminal, we will run the following:

    pip install –upgrade transformers

    Alternatively, if running directly from a Jupyter notebook, add ! to the beginning of the command.

  2. Experiment with Microsoft’s DialoGPT-medium: This LLM is dedicated to conversational applications. It was generated by Microsoft and achieved high scores when compared to other LLMs on common benchmarks. For that reason, it is also quite popular on Hugging Face’s platform, in the sense that it is downloaded frequently...

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