Create app.py

app.py

@@ -0,0 +1,22 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the model
+model_name = "cirimus/modernbert-base-go-emotions"
+classifier = pipeline("text-classification", model=model_name, top_k=None)
+
+def classify_text(text):
+    predictions = classifier(text)
+    return {pred["label"]: pred["score"] for pred in predictions[0]}
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.Textbox(lines=2, placeholder="Enter text to analyze emotions..."),
+    outputs=gr.Label(num_top_classes=5),
+    title="Emotion Classifier",
+    description="Enter a sentence to see its associated emotions and confidence scores.",
+)
+
+# Launch the app
+interface.launch()