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import gradio as gr
with gr.Blocks() as demo:
with gr.Sidebar():
gr.Markdown("# Inference Provider")
gr.Markdown("Selecciona el modelo a cargar y accede con tu cuenta de Hugging Face.")
token = gr.LoginButton("Sign in")
model_choice = gr.Dropdown(choices=["Qwen/QwQ-32B", "microsoft/phi-4", "perplexity-ai/r1-1776"],
label="Selecciona el modelo")
# Crear contenedores para cada modelo, inicialmente solo el primero es visible
container_model1 = gr.Column(visible=True)
container_model2 = gr.Column(visible=False)
container_model3 = gr.Column(visible=False)
with container_model1:
gr.load("models/Qwen/QwQ-32B", accept_token=token, provider="hyperbolic")
with container_model2:
gr.load("models/microsoft/phi-4", accept_token=token, provider="nebius")
with container_model3:
gr.load("models/perplexity-ai/r1-1776", accept_token=token, provider="fireworks-ai")
# Función para actualizar la visibilidad según el modelo seleccionado
def update_model(selected_model):
if selected_model == "Qwen/QwQ-32B":
return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
elif selected_model == "Modelo2":
return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
elif selected_model == "Modelo3":
return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
model_choice.change(fn=update_model, inputs=model_choice,
outputs=[container_model1, container_model2, container_model3])
demo.launch()
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