Frameworks & Templates
HuggingGPT (Jarvis)

HuggingGPT (Jarvis)

HuggingGPT (Jarvis) (opens in a new tab) is a collaborative system that consists of an LLM as the controller and numerous expert models as collaborative executors (from HuggingFace Hub). The workflow of our system consists of four stages:

  • Task Planning: Using ChatGPT to analyze the requests of users to understand their intention, and disassemble them into possible solvable tasks.
  • Model Selection: To solve the planned tasks, ChatGPT selects expert models hosted on Hugging Face based on their descriptions.
  • Task Execution: Invokes and executes each selected model, and return the results to ChatGPT.
  • Response Generation: Finally, using ChatGPT to integrate the prediction of all models, and generate responses.

You could use modelz template to deploy your personal HuggingGPT instance:


Please use A100(40GB) for the best performance.