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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 #15268 · 11/04/2025, 12:00 PM

#go#blockchain#cloudvpn#golang#golang_library#holepunch#ipfs#ipfs_blockchain#kubernetes#libp2p#mesh#mesh_networks#nat#networking#p2p#p2pvpn#tunnel#vpn EdgeVPN lets you create secure, decentralized private networks using peer-to-peer (p2p) connections without relying on central servers. It can build a VPN that automatically assigns IPs, includes a small DNS server, and protects your network even if tokens leak. You can also use it as a reverse proxy to share TCP services or send files securely over p2p without a VPN connection. It works well for edge devices and development, especially behind NATs, and can be integrated into your own Go programs. This helps you connect devices easily and securely across different networks without complex setup or infrastructure. https://github.com/mudler/edgevpn