5 Cool Things I Did with Local Language Models
The article discusses the advantages of using local language models over cloud-based tools. It highlights five projects that demonstrate the capabilities of running models like Llama 3.2 on personal machines. The author emphasizes the benefits of privacy and control when handling sensitive documents and data.
- ▪Local language models can be run on personal machines without the need for cloud services.
- ▪The author successfully built a private document brain using AnythingLLM to process sensitive documents locally.
- ▪Using local models allows for better privacy and control over data compared to cloud-based solutions.
Opening excerpt (first ~120 words) tap to expand
Image by Author # Introduction The first time you run ollama run llama3.2 in a terminal and watch a 7-billion-parameter model load onto your own machine — no API key, no billing dashboard, no data leaving your computer — something shifts. Not because it is technically impressive, though it is. But because it is fast, it is capable, and it is entirely yours. You own the conversation. Nobody is logging it. Nobody is charging you per token. The model does not know or care that you are offline. I have been running local models as part of my daily workflow for a while now, and what surprised me most is how often local turned out to be the better choice, not a compromise.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at KDnuggets.
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