Price: $19.95
(as of Dec 24,2024 04:28:16 UTC – Details)

ASIN ‏ : ‎ B0D14LHGZ6
Publisher ‏ : ‎ Independently published (April 8, 2024)
Language ‏ : ‎ English
Paperback ‏ : ‎ 766 pages
ISBN-13 ‏ : ‎ 979-8871928684
Item Weight ‏ : ‎ 2.76 pounds
Dimensions ‏ : ‎ 6 x 1.73 x 9 inches

Generative AI in C++: Coding Transformers and LLMs (Generative AI LLM Programming)

Generative AI, particularly Language Models (LMs) like GPT-3, have gained immense popularity in recent years for their ability to produce human-like text based on input prompts. One of the most widely used frameworks for developing such models is OpenAI’s GPT-3, which is based on the Transformer architecture.

If you’re interested in delving into the world of generative AI and building your own Language Models in C++, this post is for you. In this post, we’ll explore the basics of coding Transformers and Large Language Models (LLMs) in C++.

Transformers are a type of deep learning model that excels at capturing long-range dependencies in sequential data, making them ideal for tasks like natural language processing. LLMs, on the other hand, are a specific type of Transformer model that has been pre-trained on vast amounts of text data and fine-tuned for specific tasks.

To get started with coding Transformers and LLMs in C++, you’ll need a good understanding of deep learning concepts, particularly neural networks and attention mechanisms. You’ll also need to be familiar with libraries like TensorFlow or PyTorch, which provide the necessary tools for building and training deep learning models.

As you delve deeper into the world of generative AI programming, you’ll discover the endless possibilities that these models offer, from generating text for chatbots and virtual assistants to creating realistic dialogue for video games and movies.

So, if you’re ready to dive into the exciting world of generative AI in C++, start by learning the basics of coding Transformers and LLMs. With a little practice and experimentation, you’ll be well on your way to building your own cutting-edge Language Models that can generate human-like text with just a few lines of code.
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