Published on: 2025-05-03 03:50:09
Convenient LLMs at Home I’ve been wanting to experiment with LLMs in my homelab, but didn’t want the overhead of a dedicated GPU machine or the slowness of CPU processing. I also wanted everything to be convenient long-term: updates needed to be automated, and if the OS dies rebuilding needed to be quick and easy, etc. Running NixOS with WSL on my gaming PC seemed like the perfect solution, but I kept running into several challenges: Concerns of my vram getting locked to LLMs WSL would shut
Keywords: nixos nvidia ollama tailscale wsl
Find related items on AmazonPublished on: 2025-05-27 18:32:40
simonw/ollama-models-atom-feed. I setup a GitHub Actions + GitHub Pages Atom feed of scraped recent models data from the Ollama latest models page - Ollama remains one of the easiest ways to run models on a laptop so a new model release from them is worth hearing about. I built the scraper by pasting example HTML into Claude and asking for a Python script to convert it to Atom - here's the script we wrote together.
Keywords: atom feed github models ollama
Find related items on AmazonPublished on: 2025-06-21 18:48:15
This model requires Ollama 0.6 or later. Download Ollama Gemma is a lightweight, family of models from Google built on Gemini technology. The Gemma 3 models are multimodal—processing text and images—and feature a 128K context window with support for over 140 languages. Available in 1B, 4B, 12B, and 27B parameter sizes, they excel in tasks like question answering, summarization, and reasoning, while their compact design allows deployment on resource-limited devices. Models Text 1B parameter m
Keywords: context gemma model ollama window
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