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If you're looking for a chatbot that can generate natural language responses for various tasks and domains, you might have heard of ChatGPT, a powerful model developed by OpenAI. But did you know that there is an open-source alternative to ChatGPT that you can use for free? It's called HuggingChat, and it's created by Hugging Face, a popular AI startup that provides ML tools and AI code hub. In this article, I'll show you what HuggingChat can do, how it works, and why it's a great option for anyone interested in chatbot technology. Hugging Face Chat HuggingChat is a web-based chatbot that you can access at hf.co/chat. It's built on the LLaMa 30B SFT 6 model , which is a modified version of Meta's 30 billion parameter LLaMA model. The LLaMa model is trained on a large corpus of text from various sources, such as Wikipedia, Reddit, news articles, books, and more. It can generate text in natural language or in a specific format when prompted by the user. Huggin

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