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Source channel @githubtrending · Post #15432 · Jan 23

#jupyter_notebook#chinese_llm#chinese_nlp#finetune#generative_ai#instruct_gpt#instruction_set#llama#llm#lora#open_models#open_source#open_source_models#qlora AirLLM is a tool that lets you run very large AI models on computers with limited memory by using a smart layer-by-layer loading technique instead of traditional compression methods. You can run a 70-billion-parameter model on just 4GB of GPU memory, or even a 405-billion-parameter model on 8GB, without losing model quality. The benefit is that you can use powerful AI models on affordable hardware without expensive upgrades, and the tool also offers optional compression features that can speed up performance by up to 3 times while maintaining accuracy. https://github.com/lyogavin/airllm

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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

GitHub Trends

@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