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Source channel @githubtrending · Post #14926 · Jul 8

#jupyter_notebook#artificial_intelligence#book#large_language_models#llm#llms#oreilly#oreilly_books You can learn how to use Large Language Models (LLMs) effectively through the book *Hands-On Large Language Models* by Jay Alammar and Maarten Grootendorst. This book uses nearly 300 custom illustrations to explain key concepts and practical tools for working with LLMs, including tokenization, transformers, prompt engineering, fine-tuning, and advanced text generation. It also provides runnable code examples in Google Colab, making it easy to practice and apply what you learn. This resource helps you understand and build your own LLM applications confidently, saving you time and effort in mastering complex AI technology. It’s highly recommended for anyone wanting hands-on experience with LLMs. https://github.com/HandsOnLLM/Hands-On-Large-Language-Models

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djangoproject

@djangoproject · Post #550 · 01/15/2018, 07:05 AM

http://www.wikipython.com/other-concepts/anatomy-of-a-class/ It seems obvious, but note that you must define a class before you use it. When you create a #class, it establishes its own namespace and all its own local variables (except global definitions) exist only inside that #namespace. They do not interact with other variables of the same name outside it. This leads us to one very important “feature” of classes that you need to know. If you use the same word to designate some specific value both inside and outside the class blueprint, the instance value will take precedence when you try to use that value. #learn