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| import gradio as gr | |
| import pandas as pd | |
| from huggingface_hub.utils import HfHubHTTPError | |
| from accelerate.commands.estimate import check_has_model, create_empty_model | |
| from accelerate.utils import calculate_maximum_sizes | |
| from model_utils import get_model | |
| # We need to store them as globals because gradio doesn't have a way for us to pass them in to the button | |
| MODEL = None | |
| def get_results(model_name: str, library: str, access_token: str): | |
| global MODEL | |
| MODEL = get_model(model_name, library, access_token) | |
| data = MODEL.__repr__() | |
| title = f"## Model Representation for '{model_name}'" | |
| return [title, gr.update(visible=True, value=data)] | |
| with gr.Blocks() as demo: | |
| with gr.Column(): | |
| out_text = gr.Markdown() | |
| out = gr.Code() | |
| with gr.Row(): | |
| inp = gr.Textbox(label="Model Name or URL", value="bert-base-cased") | |
| with gr.Row(): | |
| library = gr.Radio(["auto", "transformers", "timm"], label="Library", value="auto") | |
| access_token = gr.Textbox(label="API Token", placeholder="Optional (for gated models)") | |
| with gr.Row(): | |
| btn = gr.Button("Show Model Representation") | |
| btn.click( | |
| get_results, | |
| inputs=[inp, library, access_token,], | |
| outputs=[out_text, out], | |
| ) | |
| demo.launch() | |