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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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@githubtrending · Post #14874 · 06/28/2025, 12:00 PM

#javascript#linux#macos#ocr#pot#pot_app#recognize#tauri#translate#translation#tts#windows Pot is a cross-platform translation tool that lets you quickly translate text by selecting it and using a shortcut, typing text to translate, or using OCR to translate text from screenshots. It supports many translation engines like OpenAI, Google, DeepL, and more, plus offline options. You can also add plugins to extend its features and use it on Windows, macOS, and Linux. Pot offers an API for integration with other software and works well even on Wayland systems. This makes translating easier, faster, and more flexible, helping you understand and work with multiple languages efficiently. https://github.com/pot-app/pot-desktop