# Self-Host AI Models for Customizing and Privacy
It is very east now to run and fine-tune your own LLM (Large Language Model) like ChatGPT at home. The benefit is learning how it all works and the privacy to fine tune a model to your needs. Instead of training OpenAI's for them.
Here are some projects to get you started with self-hosted LLMs on a basic NVIDIA GPU or even with just CPU.
## Web Interfaces and API Interfaces
[Text Generation WebUI](https://github.com/oobabooga/text-generation-webui)
[h2oGFPT](https://github.com/h2oai/h2ogpt)
[localai.io](https://localai.io)
[LLaMa2-chatbot](https://github.com/a16z-infra/llama2-chatbot)
[Petals Distributed Models](https://petals.dev/)
## Voice Assistant
[Willow](https://github.com/toverainc/willow)
[HomeAssistant](https://www.home-assistant.io/)
## Models
[HuggingFace](https://huggingface.co/models)
## DataSets for Training
[LLMDataHub](https://github.com/Zjh-819/LLMDataHub)
[HuggingFace DataSets](https://huggingface.co/datasets)
## Testing
[TermGPT](https://github.com/Sentdex/TermGPT)
#selfhost #self-host #llm #ai #llama2 #gpt #linux #diy
Oops links got jumbled.
## Web Interfaces and API Interfaces
[Text Generation WebUI](https://github.com/oobabooga/text-generation-webui)
[h2oGFPT](https://github.com/h2oai/h2ogpt)
[localai.io](https://localai.io)
[LLaMa2-chatbot](https://github.com/a16z-infra/llama2-chatbot)
[Petals Distributed Models](https://petals.dev/)
After all. If you help train OpenAI you are indirectly helping Worldcoin 😉
