Create app.py

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+import pandas as pd
+import joblib
+import datasets
+
+
+inputs = [gr.Dataframe(row_count = (2, "dynamic"), col_count=(4,"dynamic"), label="Input Data", interactive=1)]
+
+outputs = [gr.Dataframe(row_count = (2, "dynamic"), col_count=(1, "fixed"), label="Predictions", headers=["Failures"])]
+
+model = joblib.load("model.pkl")
+
+# we will give our dataframe as example
+df = datasets.load_dataset("merve/supersoaker-failures")
+df = df["train"].to_pandas()
+
+def infer(input_dataframe):
+  return pd.DataFrame(model.predict(input_dataframe))
+
+gr.Interface(fn = infer, inputs = inputs, outputs = outputs, examples = [[df.head(2)]]).launch()