This tutorial provides a step-by-step guide for installing a ChatGPT-like large language model (LLM) locally on Apple devices such as iPad or iPhone. The guide explains the prerequisites, including having at least 8GB of RAM and free local storage space. It then walks through the process of installing Testflight and LLMFarm, downloading a pre-trained Mistral-7B model, setting up LLMFarm to use the model, configuring the chat settings, and testing the LLM. The tutorial highlights the benefits of hosting an LLM locally, emphasizing privacy and portability. The Mistral-7B model is recommended for its performance and smaller size. The tutorial includes links to additional resources, such as a video walkthrough for interactive setup.
| Signal | Change | 10y horizon | Driving force |
|---|---|---|---|
| Using LLMs locally on iPad or iPhone | Use of local language models on Apple devices | Increased availability and privacy of LLMs on devices | Privacy concerns and portability of devices |
| Install LLMs locally on Apple devices | Shift from using cloud-based language models | Increased control over data and offline access | Privacy concerns and portability of devices |
| Use of TestFlight app for LLM installation | Adoption of TestFlight for app testing | Improved app testing and development process | Technical convenience and efficiency |
| Select pre-trained models from huggingface.co | Access to a variety of pre-trained models | Increased options for model selection | Availability and diversity of pre-trained models |
| Configuring LLM applications for specific models | Customization of LLM applications for user’s needs | Tailored user experiences with LLM capabilities | User preference and specific use cases |
| Privacy and data security concerns driving LLM usage | Increased emphasis on privacy and data security | Protection of personal data and conversations | Growing awareness of privacy risks |
| Portability and versatility of iPads and iPhones | Preference for portable and versatile devices | Ease of carrying and using LLMs anywhere | User preference for lightweight devices |
| The efficiency of Mistral-7B model for Apple devices | Improved model performance with limited computing | Better performance with limited resources | Optimization for Apple devices |
| Availability of video tutorials for LLM setup | Increased accessibility and learning opportunities | Ease of learning and following LLM setup process | Enhanced education and support for users |