Artificial intelligence (AI) is rapidly evolving, and language models (LMs) are becoming increasingly capable of helping us solve complex AI tasks. As the complexity of AI tasks increases, so does the need for LMs to interface with numerous AI models. This is where HuggingGPT comes in. In this article, we'll take a closer look at HuggingGPT and how it can help you solve complex AI tasks. HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in HuggingFace HuggingGPT is a collaborative system that consists of an LLM as the controller and numerous expert models as collaborative executors. The workflow of the HuggingGPT system consists of four stages: Task Planning, Model Selection, Task Execution, and Response Generation. Let's take a closer look at each of these stages. Task Planning The first stage of the HuggingGPT system is Task Planning. Using ChatGPT, HuggingGPT analyzes the requests of users to understand their intention, and disassemble them into possible solvable ta
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