Update app.py

app.py

@@ -17,7 +17,7 @@ bi_encoder.max_seq_length = 256
 top_k = 3
 
 # Load your fine-tuned model and tokenizer
-model_name = "legacy107/flan-t5-large-ia3-wiki-merged"
+model_name = "legacy107/flan-t5-large-ia3-wiki2-100-merged"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = T5ForConditionalGeneration.from_pretrained(model_name)
 max_length = 512
@@ -98,7 +98,7 @@ def generate_answer(question, context, ground):
     # Decode and return the generated answer
     generated_answer = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
 
-    return generated_answer, context, ground
+    return generated_answer, context
 
 
 # Define a function to list examples from the dataset
@@ -122,8 +122,7 @@ iface = gr.Interface(
     ],
     outputs=[
         Textbox(label="Generated Answer"),
-        Textbox(label="Retrieved Context"),
-        Textbox(label="Ground Truth")
+        Textbox(label="Retrieved Context")
     ],
     examples=list_examples()
 )