Create app.py

app.py

@@ -0,0 +1,32 @@
+from transformers import pipeline
+import spacy
+import gradio as gr
+
+# Initialize the classifier
+classifier = pipeline(
+    "sentiment-analysis", 
+    model="wjbmattingly/human-remains-classifier-modernbert-large",
+    max_length=4000,
+    truncation=True
+)
+
+# Define the prediction function
+def predict_text(text):
+    result = classifier(text)
+    return result[0]['label'], result[0]['score']
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=predict_text,
+    inputs=gr.Textbox(label="Enter text to analyze"),
+    outputs=[
+        gr.Label(label="Classification"),
+        gr.Number(label="Confidence Score")
+    ],
+    title="Human Remains Text Classifier",
+    description="Enter text to classify whether it contains references to human remains."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()