Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load your model from Hugging Face
+classifier = pipeline(
+    "text-classification",
+    model="username/model-name",       # Replace with your Hugging Face username/model
+    tokenizer="username/model-name",   # Same here
+    top_k=None                         # Return all labels with scores
+)
+
+# Define the prediction function
+def classify_numbers(n1, n2, n3):
+    input_str = f"{n1}, {n2}, {n3}"
+    result = classifier(input_str)
+    # Format the results nicely
+    output = {item["label"]: round(item["score"], 3) for item in result[0]}
+    return output
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=classify_numbers,
+    inputs=[
+        gr.Textbox(label="Input 1"),
+        gr.Textbox(label="Input 2"),
+        gr.Textbox(label="Input 3")
+    ],
+    outputs="label",
+    title="Number Classifier",
+    description="Enter 3 numbers or symbols (e.g., 3.14, pi, 2) to classify them."
+)
+
+iface.launch()