...     "What does 🤗 Transformers provide?",
...     "🤗 Transformers provides interoperability between which frameworks?",
... ]
for question in questions:
...     inputs = tokenizer(question, text, add_special_tokens=True, return_tensors="pt")
...     input_ids = inputs["input_ids"].tolist()[0]
...     outputs = model(**inputs)
...     answer_start_scores = outputs.start_logits
...     answer_end_scores = outputs.end_logits
...     # Get the most likely beginning of answer with the argmax of the score
...     answer_start = torch.argmax(answer_start_scores)
...     # Get the most likely end of answer with the argmax of the score
...     answer_end = torch.argmax(answer_end_scores) + 1
...     answer = tokenizer.convert_tokens_to_string(
...         tokenizer.convert_ids_to_tokens(input_ids[answer_start:answer_end])
