Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the text classification model
+classifier = pipeline('text-classification', model='ardavey/bert-large-depression-classification-model')
+
+# Define a function for text classification
+def classify_text(text):
+    predictions = classifier([text])
+    label = 'Depressed' if predictions[0]['label'] == 'LABEL_1' else 'Not Depressed'
+    score = predictions[0]['score']
+    return f"Prediction: {label}, Score: {score:.4f}"
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.Textbox(lines=5, placeholder="Enter your text here..."),
+    outputs="text",
+    title="Depression Text Classifier",
+    description="Enter a text sample to check for signs of depression."
+)
+
+# Launch the Gradio app
+interface.launch()