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Source channel @githubtrending · Post #14909 · Jul 3

#other#agent#llm#rag Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research. https://github.com/datawhalechina/happy-llm

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Libreware

@libreware · Post #1321 · 08/29/2024, 08:23 PM

__ __ _ __ / /_____ ____ / /_(_) /__ / __/ __ \/ __ \/ __/ / //_/ / /_/ /_/ / /_/ / /_/ / ,< \__/\____/\____/\__/_/_/|_| tootik v0.12.0 [https://github.com/dimkr/tootik] tootik is a federated nanoblogging service for the small internet. tootik allows people to participate in the fediverse using their Gemini, Gopher or Finger client of choice and makes the fediverse lighter, more private and more accessible. tootik's interface strips content to bare essentials (like text and links), puts the users in control of the content they see and tries to "slow down" the fediverse to make it more compatible with the slower pace of the small internet. It's a single executable that handles both the federation (using ActivityPub) and the frontend (using Gemini) aspects, while sqlite takes care of persistency. It should be lightweight and efficient enough to host a small community even on a cheap server, and hopefully, be easy to hack on. tootik implements only a small subset of ActivityPub, and probably doesn't really conform to the spec. Changelog: [https://github.com/dimkr/tootik/releases/tag/0.12.0] #Gemini#Gopher#Guppy#Fediverse#ActivityPub