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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 #129 · 08/31/2016, 03:36 PM

https://pypi.python.org/pypi/numpy #NumPy is a general-purpose #array-processing package designed to efficiently manipulate large #multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional #arrays. NumPy is built on the #Numeric code base and adds features introduced by #numarray as well as an extended #C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose #data-base applications.