New to Gradio? Start here: Getting Started

To install Gradio from main, run the following command:

pip install https://gradio-builds.s3.amazonaws.com/35bc484c1744ff435057642495be05fb3e839b6e/gradio-4.35.0-py3-none-any.whl

*Note: Setting share=True in launch() will not work.

load

gradio.load(···)

Constructs a demo from a Hugging Face repo. Can accept model repos (if src is "models") or Space repos (if src is "spaces"). The input and output components are automatically loaded from the repo. Note that if a Space is loaded, certain high-level attributes of the Blocks (e.g. custom `css`, `js`, and `head` attributes) will not be loaded.

import gradio as gr
demo = gr.load("gradio/question-answering", src="spaces")
demo.launch()

Parameter	Description
`name` str required	the name of the model (e.g. "gpt2" or "facebook/bart-base") or space (e.g. "flax-community/spanish-gpt2"), can include the `src` as prefix (e.g. "models/facebook/bart-base")
`src` str \| None default: None	the source of the model: `models` or `spaces` (or leave empty if source is provided as a prefix in `name`)
`hf_token` str \| None default: None	optional access token for loading private Hugging Face Hub models or spaces. Find your token here: https://huggingface.co/settings/tokens. Warning: only provide this if you are loading a trusted private Space as it can be read by the Space you are loading.
`alias` str \| None default: None	optional string used as the name of the loaded model instead of the default name (only applies if loading a Space running Gradio 2.x)