How to run an LLM on your PC, not in the cloud, in less than 10 minutes
You can easily set up and run large language models (LLMs) on your PC using tools like Ollama, LM Suite, and Llama.cpp. Ollama supports AMD GPUs and AVX2-compatible CPUs, with straightforward installation across different systems. It offers commands for managing models and now supports select AMD Radeon cards.
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In less than 10 minutes, you can run a large language model (LLM) on your PC locally using tools like Ollama, LM Suite, and Llama.cpp. These tools make it easy to set up LLMs on Windows, Linux, and Mac systems. While dedicated accelerators like Nvidia GPUs are optimal for performance, Ollama also supports AMD GPUs and AVX2-compatible CPUs. The installation process for Ollama is straightforward across different operating systems. You can start with models like Mistral 7B by running simple commands in PowerShell or a terminal emulator. Quantization techniques can help reduce memory requirements for running LLMs, allowing them to operate on systems with limited resources. Ollama provides commands for managing, updating, and removing installed models, similar to Docker CLI. Additionally, Ollama now supports select AMD Radeon 6000-and 7000-series cards. Stay tuned for more insights on utilizing LLMs from The Register.
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6 commentsbetter still you can the use python to call it with langchain chatollama and build anything you want with a little help from claude and chatgpt or codeqwen if you want to do it all locally.
absolute AI don. impress the ladies with that one, you'll be beating them off with a stick when they see it in action.
just need plenty of VRAM after that.
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