Why Install and Host Large Langue Model on your Computer

I saw questions on couple of places about hosting your own LLM and thought I’d chime in with my two cents. Hosting your own Large Language Model (LLM) is pretty cool for a couple of reasons. Privacy is a big one for many folks. If you’re working with sensitive data, you definitely don’t want to send it over to OpenAI or Microsoft. Plus, doing it yourself is a rewarding learning experience.

People are using local Large Language Models (LLMs) for various reasons, primarily driven by personal interests and specific use cases. A significant motivation is the curiosity to explore the capabilities of these models and integrate them into personal projects. Some users focus on hobbyist applications, like generating code, storytelling, or enhancing creativity in music and art. Others are interested in more practical applications, such as querying technical documents, assisting with coding, or generating content for games and interactive experiences.

Jumping in on the LLM hosting! Installing and hosting large langue model on PC or Mac is great if you’re into integrating them into personal projects, especially if you’re looking to have more control and avoid limitations of cloud services. You can download different models, but typically you’ll run one at a time due to hardware constraints.

There are couple of reasons to install and run LLMs locally

• Exploring Coding Solutions: Some users are experimenting with code models like CodeLLaMa-34B to assist in coding tasks and programming challenges.
• Hobby and Entertainment: Many are using LLMs as a hobby, for fun or as a part of their personal entertainment, like creating stories, character generation, or role-playing.
• Robot Interaction: Users are interfacing LLMs with robots they are building, using the models for communication or control purposes.
• Educational Use: Users are utilizing LLMs to understand complex documents like PDFs and technical papers, querying and extracting information from them.
• Creating Personalized Content: Some are using LLMs for creating music, videos, art, or helping in writing projects like books.
• Personal Assistants: LLMs are being used to build personal assistants for various tasks like coding, data analysis, and even for general conversation.
• Privacy Concerns: Users are opting for local models over cloud-based solutions for privacy reasons, especially when dealing with sensitive or personal data.
• Offline Access: The ability to use LLMs offline is a significant factor, especially for those needing access to AI capabilities without an internet connection.
• Uncensored Role play Content: Many users use the advantage of local LLMs in generating uncensored role play content, which is restricted on cloud-based platforms.
• Customization and Experimentation: Enthusiasts are experimenting with local LLMs for the sake of learning and customization, exploring the possibilities and limitations of these models.

These varied use cases highlight the growing interest in local LLMs for both personal and experimental purposes, driven by factors like privacy, customization, offline access, and the desire to integrate AI into personal projects and hobbies.

This field is moving super fast, so it’s hard to keep up with the latest and greatest. I started with LLaMA, but there are loads of options. Voice interaction is possible, but you might need to dig around for specific projects, like Willow for example.

Regarding the context, these models don’t really retain long conversations. It’s more about short bursts of interaction. LMStudio studio is a good starting point for setup and running models. It’s user-friendly but a bit limited in tinkering.

It can be overwhelming at first, especially with how fast everything’s developing. The best advice I can give is just to start experimenting, ask questions, and be prepared for a bit of trial and error. Good luck!