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app.py

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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")

requirements.txt

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+datasets
+gradio