Run LLM on a local server

Expert DevOps engineers utilize Local LLMs as a more efficient and cost-effective alternative to utilizing ChatGPT services. These local models allow access to the same AI technology without relying on external service providers, enabling significant cost savings by utilizing internal resources. Moreover, Local LLMs, being hosted locally and independent of internet connectivity, offer heightened levels of privacy and security compared to cloud-based services like ChatGPT.

For programmers and researchers, numerous open-source LLMs and machine learning models are accessible through platforms like Hugging Face, providing viable alternatives to ChatGPT. However, utilizing these models may necessitate programming skills and slightly more powerful hardware than standard Chromebooks, typically requiring mid-range CPUs with at least 8GB of RAM. For an optimal experience, leveraging GPUs with CUDA drivers is recommended, with NVIDIA Graphics Cards being suitable for most PCs or laptops.

Fortunately, accessing these resources is highly feasible for average users and hobbyists as well. Ollama.ai provides a streamlined approach for downloading and running LLMs on personal computers, primarily targeting MacOS and Linux users, with Windows compatibility forthcoming. Windows users can still utilize Ollama by installing Windows System for Linux and activating Virtual Machine Platform.

Ollama operates within the terminal, offering liteLLM for hosting locally hosted APIs, facilitating seamless app integration for hobbyists and developers. Users seeking a web browser experience can explore various web user interfaces like anything-llm.

It’s advisable to explore alternatives like Ollama instead of relying solely on corporate-controlled LLMs. Ollama is user-friendly, free, and ensures complete privacy, offering a safer option compared to potentially invasive alternatives.