Introduction to LLM


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7.3 Integrating Multimodal Models

A preview from Chapter 7.3: Discover how multimodal models fuse text, images, audio, and video to unlock richer AI capabilities beyond text-only LLMs.
2024-10-09

7.0 Future Outlook and Challenges

A preview from Chapter 7: Explore the future of large language models—ethics, efficiency, multimodal AI, and responsible governance beyond scaling.
2024-10-06

6.2 Simple Python Experiments with LLMs

A preview from Chapter 6.2: Learn how to run large language models with Hugging Face, OpenAI, Google Cloud, and Azure using just Python and a few lines of code.
2024-10-05

6.1 Introducing Open-Source Tools and APIs

A preview from Chapter 6.1: Explore Hugging Face, OpenAI, Google Cloud Vertex AI, and Azure Cognitive Services—leading tools to bring LLMs into your projects.
2024-10-04

6.0 Hands-On with LLMs

A preview from Chapter 6: Learn how to run large language models yourself with open-source libraries, cloud APIs, and Python—making LLMs accessible to everyone.
2024-10-02

4.4 How LLMs Write Code: The Rise of AI-Powered Programming Assistants

Explore how large language models (LLMs) generate and complete code from natural-language prompts, and what it means for the future of software development.
2024-09-27

2.3 Key LLM Models: BERT, GPT, and T5 Explained

Discover the main differences between BERT, GPT, and T5 in the realm of Large Language Models (LLMs). Learn about their unique features, applications, and how they contribute to various NLP tasks.
2024-09-10

1.1 Understanding Large Language Models (LLMs): Definition, Training, and Scalability Explained

Explore the fundamentals of Large Language Models (LLMs), including their structure, training techniques like pre-training and fine-tuning, and the importance of scalability. Discover how LLMs like GPT and BERT work to perform NLP tasks like text generation and translation.
2024-09-03

A Guide to LLMs (Large Language Models): Understanding the Foundations of Generative AI

Learn about large language models (LLMs), including GPT, BERT, and T5, their functionality, training processes, and practical applications in NLP. This guide provides insights for engineers interested in leveraging LLMs in various fields.
2024-09-01