Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+import pandas as pd
+
+def filter_by_hardware_or_bits(df, hardware=None, bits=None):
+    if hardware is None and bits is None:
+        raise ValueError("At least one of 'hardware' or 'bits' must be specified.")
+    
+    hardware_mask = df['hardware'] == hardware if hardware is not None else pd.Series([True] * len(df))
+    bits_mask = df['bits'] == bits if bits is not None else pd.Series([True] * len(df))
+    
+    combined_mask = hardware_mask & bits_mask
+    
+    filtered_df = df[combined_mask]
+    
+    return filtered_df
+
+def filter_dataframe(hardware, bits):
+    filtered_df = filter_by_hardware_or_bits(quantization_data, hardware=hardware, bits=bits)
+    return filtered_df
+
+demo = gr.Interface(
+    fn=filter_dataframe,
+    inputs=[
+        gr.Dropdown(choices=quantization_data['hardware'].unique().tolist(), label="hardware"),
+        gr.Dropdown(choices=quantization_data['bits'].unique().tolist(), label="bits"),
+    ],
+    outputs=gr.Dataframe(headers=list(quantization_data.columns)),
+    title="Quantization methods",
+    description="Pick a quantization method based on your hardware and k-bit quantization."
+)
+
+demo.launch()