first

app.py

@@ -14,18 +14,9 @@ def answer_question(context, question):
   # Encode the context and question
   inputs = tokenizer(context, question, return_tensors="pt")
 
-  # Perform question answering
-  outputs = model(**inputs)
-
-  # Get the predicted start and end token positions
-  start_scores, end_scores = outputs.start_logits, outputs.end_logits
-
-  # Decode the answer based on predicted positions
-  answer_start = torch.argmax(start_scores)
-  answer_end = torch.argmax(end_scores) + 1
 
   # Get answer tokens and convert them to string
-  answer = tokenizer.convert_ids_to_tokens(inputs["input_ids"][0][answer_start:answer_end])
+  answer = tokenizer.convert_ids_to_tokens(inputs["input_ids"][0])
   answer = "".join(answer)
 
   return answer