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| import gradio as gr | |
| from datasets import load_dataset | |
| import pandas as pd | |
| db = load_dataset("nicholasKluge/model-library", split='main') | |
| db = db.to_pandas() | |
| def display_model_information(value): | |
| """ | |
| This function will display the model information for the selected model | |
| """ | |
| # If the value is empty, return None | |
| if value == '': | |
| return None, None | |
| # Get the model information | |
| info = db.iloc[int(db[db.model_name_string == value].index.values)] | |
| # Create the model details and model info | |
| model_details = f"""## Model Details | |
| - Name: {info.model_name_url} | |
| - Model Size: {info.model_size_string} | |
| - Dataset: {info.dataset} | |
| - Input/Output Format: {info.data_type} | |
| - Research Field: {info.research_field} | |
| - Contains an Impact Assessment: {info.risks_and_limitations} | |
| - Associated Risks: ☣️ {info.risk_types} ☣️ | |
| - Date of Publication: {info.publication_date} | |
| - Organization: {info.organization_and_url} ({info.institution_type}) | |
| - Country/Origin: {info.country} | |
| - License: {info.license} | |
| - Publication: {info.paper_name_url} | |
| """ | |
| model_info = f"""## Description | |
| {info.model_description} | |
| ## Organization | |
| {info.organization_info} | |
| """ | |
| return model_details, model_info | |
| with open('data/risks_list.md', 'rb') as f: | |
| risk_text = f.read().decode('utf-8')[44:] | |
| with gr.Blocks(theme='HaleyCH/HaleyCH_Theme') as demo: | |
| gr.Markdown("""<h1><center>Model Library</h1></center>""") | |
| gr.HTML("""<center><img src="file/assets/logo.png" width="200" height="200"></center>""") | |
| gr.HTML(f"<center><div style='max-width: 50%;'>The Model Library is a project that maps the risks associated with modern machine \ | |
| learning systems. Here, we assess some of the most recent and capable AI systems ever created. \ | |
| We have already mapped {len(db)} models from the AI community!</div></center>") | |
| dropdown = gr.Dropdown( | |
| choices=db.model_name_string.tolist(), | |
| label="Choose a model", | |
| info="These are the models we have already produced reports." | |
| ) | |
| display = gr.Button(value="Display") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| model_details = gr.Markdown() | |
| with gr.Column(scale=4): | |
| model_info = gr.Markdown() | |
| with gr.Accordion(label="Mapped Risks", open=False): | |
| gr.Markdown(risk_text) | |
| gr.HTML(f"<center><div style='max-width: 50%;'>If you would like to add a model, read our\ | |
| documentation and submit a PR on <a href='https://github.com/Nkluge-correa/ModelLibrary' \ | |
| target='_blank'>GitHub</a>!</div></center>") | |
| display.click(fn=display_model_information, inputs=dropdown, outputs=[model_details, model_info]) | |
| demo.launch(debug=True, favicon_path="file/assets/favicon.ico") |