11 Building locally running LLM-based applications using GPT4All
This chapter covers
- Introducing GPT4All
- Loading a model from GPT4All
- Holding a conversation with a model from GPT4All
- Creating a web UI for GPT4All using Gradio
You’ve learned about constructing large language model (LLM)–based applications using models from OpenAI and Hugging Face. Although these models have transformed natural language processing (NLP), there are notable drawbacks. Primarily, privacy emerges as a critical concern for businesses. Relying on third-party-hosted models introduces a security risk because your conversations would be transmitted to these external companies, raising apprehension for businesses that deal with sensitive data. Also, the challenge of integrating these models with your private data exists, and even if that challenge is met, the initial privacy concern resurfaces.
A more effective approach is to execute the models locally on your computer. This gives you control of the destination of your private data and enables you to fine-tune the models to suit your specific data requirements. But running an LLM often requires graphics processing units (GPUs), constituting a significant investment.