This tutorial provides a step-by-step guide on building an LLM router to balance the use of high-quality closed LLMs like GPT-4 and cost-effective open-source LLMs, achieving high response quality while minimizing costs. The approach includes preparing labeled data, finetuning a causal LLM classifier, and offline evaluation using the RouteLLM framework.
This project implements a real-time face recognition system using OpenCV and the face_recognition library. The system detects faces from a video stream, recognizes previously seen faces, and displays metadata about each recognized face. It supports both Raspberry Pi cameras and USB webcams.
This tutorial introduces promptrefiner, a tool created by Amirarsalan Rajabi that uses the GPT-4 model to create perfect system prompts for local LLMs.
- GitHub repository for a tutorial series called "0 to LitGPT."
- Provides an overview of how to get started with LitGPT, which is an open-source implementation of GPT-3.
- Offers various resources such as codes, issues, pull requests, actions, security features, insights, and more related to the LitGPT project.
- Provides an overview of how to get started with LitGPT, which is an open-source implementation of GPT-3.
- Offers various resources such as codes, issues, pull requests, actions, security features, insights, and more related to the LitGPT project.
