Gradio is an open-source Python library that facilitates the creation of interactive web-based interfaces for machine learning (ML) models. A graphical user interface on top of ML models provides a better understanding of the inputs, constraints and outputs by nontechnical audiences. Gradio has gained a lot of traction in the generative AI space, as it is one of the tools that makes generative models so accessible to experiment with. Usually, we put technologies into the Trial ring when we’ve seen them used in production at least once. Gradio's purpose and strength are experimentation and prototyping, and we’ve used it for that purpose many times. Recently, one of our teams even used it to help a client with live demonstrations at big events. We’re very happy with Gradio's capabilities for those use cases, and therefore move it into the Trial ring.
Gradio is an open-source Python library that allows for the quick-and-easy creation of interactive web-based interfaces for ML models. A graphical user interface on top of ML models enables a better understanding of the inputs, constraints and outputs by nontechnical audiences. Gradio supports many input and output types — from text and images to voice — and has emerged as a go-to tool for rapid prototyping and model evaluation. Gradio lets you easily host your demos on Hugging Face or run them locally and enable others to access your demo remotely with a "XXXXX.gradio.app" url. For example, the famous DALL-E mini experiment leverages Gradio and is hosted on Hugging Face Spaces. Our teams have been happy using this library for experimentation and prototyping, which is why we put it in Assess.
