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test
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app.py
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import gradio as gr
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import requests
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import json
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import logging
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from optimum.neuron import utils
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# Set up logging
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logging.basicConfig(level=logging.INFO)
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def get_model_info(model_id
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config_list = utils.get_hub_cached_entries(model_id=model_id, mode="inference")
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return config_list
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if __name__ == "__main__":
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iface
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import gradio as gr
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import logging
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from optimum.neuron import utils
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import os
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# Set up logging
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logging.basicConfig(level=logging.INFO)
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def get_model_info(model_id):
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"""Retrieve configuration details for a specific model."""
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if not model_id:
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return "No model selected"
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config_list = utils.get_hub_cached_entries(model_id=model_id, mode="inference")
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return config_list
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def get_model_list():
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"""Retrieve list of cached models."""
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return utils.get_hub_cached_models(mode="inference")
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def create_model_list_interface():
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"""Create a Gradio interface with model list as clickable buttons."""
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# Get the model list and sort alphabetically by full model ID
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models = sorted(get_model_list(), key=lambda x: (x[1] + x[2]).lower())
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print(models)
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# Prepare model IDs for buttons
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model_ids = [f"{org}/{name}" for (arch, org, name) in models]
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# Create the interface
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with gr.Blocks() as iface:
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with gr.Tab("Model List"):
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# Buttons
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with gr.Row():
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buttons = gr.Radio(
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choices=model_ids,
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label="Select a Model"
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)
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# Output for model details
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output = gr.Textbox(label="Model Configuration", lines=20)
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# Connect model selection to output
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buttons.change(
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fn=get_model_info,
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inputs=buttons,
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outputs=output
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)
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return iface
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# Launch the interface
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if __name__ == "__main__":
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iface = create_model_list_interface()
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iface.launch()
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