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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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ALL About RSS

@AboutRss · Post #1051 · 06/13/2021, 01:00 PM

本周 RSS #玩家#教程 分享 1️⃣「搭建一个 rss 订阅 bot」 https://ednovas.xyz/2021/06/07/rss_bot/ 2️⃣「How to add a RSS feed to a #rails blog」 https://webdevchallenges.com/how-to-add-a-rss-feed-to-a-rails-blog 3️⃣「How to use #GitHub actions and Contentful webhooks to show your latest blog posts on your GitHub profile README」 https://whitep4nth3r.com/blog/how-to-github-actions-contentful-webhooks-to-show-latest-blog-posts-readme 4️⃣「How To Create RSS Feeds In #Golang」 https://medium.com/canopas/how-to-create-rss-feeds-in-golang-43a99fa302e9

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@githubtrending · Post #15303 · 12/04/2025, 07:00 PM

#ruby#hotwire#kanban#rails#ruby Fizzy is an open-source Kanban tool by 37signals that helps you visually track tasks and ideas using boards with columns. You can set it up easily, run it locally or with MySQL, and test it with built-in commands. It supports email previews and web push notifications for updates. Fizzy is designed to be simple, modern, and customizable, letting you self-host for full control over your data. It also offers a companion SaaS gem for billing and production setups. This means you get a flexible, transparent way to manage projects and workflows, with the option to run it yourself or use a hosted service. https://github.com/basecamp/fizzy