...     answer_start = tf.argmax(answer_start_scores, axis=1).numpy()[0]
...     # Get the most likely end of answer with the argmax of the score
...     answer_end = tf.argmax(answer_end_scores, axis=1).numpy()[0] + 1
...     answer = tokenizer.convert_tokens_to_string(
...         tokenizer.convert_ids_to_tokens(input_ids[answer_start:answer_end])
...     )
...     print(f"Question: {question}")
...     print(f"Answer: {answer}")
Question: How many pretrained models are available in 🤗 Transformers?
Answer: over 32 +
Question: What does 🤗 Transformers provide?
Answer: general - purpose architectures
Question: 🤗 Transformers provides interoperability between which frameworks?
Answer: tensorflow 2. 0 and pytorch
```
Language Modeling
Language modeling is the task of fitting a model to a corpus, which can be domain specific. All popular
