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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
Search: #modulefinder
@djangoproject · Post #154 · 09/04/2016, 12:14 PM
https://docs.python.org/2/library/modulefinder.html This #module provides a #ModuleFinder class that can be used to determine the set of modules imported by a script. modulefinder.py can also be run as a script, giving the filename of a Python script as its argument, after which a report of the imported modules will be printed.
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@djangoproject · Post #145 · 09/02/2016, 03:28 AM
https://docs.python.org/3/library/modulefinder.html This module provides a #ModuleFinder class that can be used to determine the set of #modules#imported by a #script. modulefinder.py can also be run as a script, giving the #filename of a Python script as its argument, after which a report of the imported modules will be printed.