Update app.py

added support for the large version

app.py

@@ -1,27 +1,37 @@
 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)
+# Define model names
+models = {
+    "ModernBERT Base (Go-Emotions)": "cirimus/modernbert-base-go-emotions",
+    "ModernBERT Large (Go-Emotions)": "cirimus/modernbert-large-go-emotions"
+}
 
-def classify_text(text):
+# Function to load the selected model
+def classify_text(text, model_name):
+    classifier = pipeline("text-classification", model=models[model_name], top_k=None)
     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...", 
-        value="I am thrilled to be a part of this amazing journey!"
-    ),
+    inputs=[
+        gr.Dropdown(
+            list(models.keys()),
+            label="Select Model",
+            value="ModernBERT Base (Go-Emotions)"
+        ),
+        gr.Textbox(
+            lines=2,
+            placeholder="Enter text to analyze emotions...",
+            value="I am thrilled to be a part of this amazing journey!"
+        )
+    ],
     outputs=gr.Label(num_top_classes=5),
-    title="Emotion Classifier",
-    description="Enter a sentence to see its associated emotions and confidence scores.",
+    title="ModernBERT Emotion Classifier",
+    description="Select a model and enter a sentence to see its associated emotions and confidence scores.",
 )
 
-
 # Launch the app
 interface.launch()