gradio/guides/02_building-interfaces/04_advanced-interface-features.md
aliabid94 d9e9ae43f5
Guide fixes, esp. streaming audio (#5534)
* changes

* changes

* add changeset

* add changeset

* add requirements.txt

* req.txt

* guide fix

* backwards compat

* lint

* notebooks

---------

Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com>
Co-authored-by: Abubakar Abid <abubakar@huggingface.co>
2023-09-18 16:52:39 -07:00

1.4 KiB

Advanced Interface Features

Loading Hugging Face Models and Spaces

Gradio integrates nicely with the Hugging Face Hub, allowing you to load models and Spaces with just one line of code. To use this, simply use the load() method in the Interface class. So:

  • To load any model from the Hugging Face Hub and create an interface around it, you pass "model/" or "huggingface/" followed by the model name, like these examples:
gr.Interface.load("huggingface/gpt2").launch();
gr.Interface.load("huggingface/EleutherAI/gpt-j-6B",
    inputs=gr.Textbox(lines=5, label="Input Text")  # customizes the input component
).launch()
  • To load any Space from the Hugging Face Hub and recreate it locally (so that you can customize the inputs and outputs for example), you pass "spaces/" followed by the model name:
gr.Interface.load("spaces/eugenesiow/remove-bg",
                  inputs="webcam",
                  title="Remove your webcam background!").launch()

One of the great things about loading Hugging Face models or spaces using Gradio is that you can then immediately use the resulting Interface object just like function in your Python code (this works for every type of model/space: text, images, audio, video, and even multimodal models):

io = gr.Interface.load("models/EleutherAI/gpt-neo-2.7B")
io("It was the best of times")  # outputs model completion