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import gradio as gr
from gradio_huggingfacehub_search import HuggingfaceHubSearch
example = HuggingfaceHubSearch().example_value()
def predict(hub_repo_id):
print("hub_repo_id", hub_repo_id)
return hub_repo_id
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
search_in = HuggingfaceHubSearch(
label="Search Huggingface Hub",
placeholder="Search for models on Huggingface",
search_type="model",
)
btn = gr.Button("Run")
with gr.Column():
search_out = HuggingfaceHubSearch(label="Search Huggingface Hub")
gr.on(
[btn.click, search_in.submit],
fn=predict,
inputs=[search_in],
outputs=[search_out],
)
if __name__ == "__main__":
demo.launch()
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