Update app.py

app.py

@@ -1,19 +1,21 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the model
-model = pipeline("text-generation", model="Rishitha0208/new-llm-for-advanced-materials")
+# Load the question-answering model
+model = pipeline("question-answering", model="Rishitha0208/new-llm-for-advanced-materials")
 
-def generate_text(prompt):
-    return model(prompt, max_length=50, num_return_sequences=1)[0]['generated_text']
+def answer_question(question):
+    # Generate an answer from the model
+    result = model(question=question, context="")  # Provide an empty context if not required
+    return result['answer']
 
 # Define the Gradio interface
 interface = gr.Interface(
-    fn=generate_text,
-    inputs=gr.Textbox(lines=2, placeholder="Enter your text here..."),
+    fn=answer_question,
+    inputs=gr.Textbox(lines=2, placeholder="Enter your question here...", label="Question"),
     outputs="text",
-    title="Text Generation Model",
-    description="A text generation model using Hugging Face Transformers."
+    title="Polymer Knowledge Model",
+    description="A model fine-tuned to answer questions about polymers."
 )
 
 # Launch the interface