readme: ---
  datasets:
  - squad_v2
  language: en
  license: mit
  pipeline_tag: question-answering
  tags:
  - roberta
  - question-answering
  ---
  # Roberta base model for QA (SQuAD 2.0)
  
  This model uses [roberta-base](https://huggingface.co/roberta-base).
  
  ## Training Data
  The models have been trained on the [SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/) dataset.
  
  It can be used for question answering task.
  
  ## Usage and Performance
  The trained model can be used like this:
  ```python
  from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
  
  # Load model & tokenizer
  roberta_model = AutoModelForQuestionAnswering.from_pretrained('navteca/roberta-base-squad2')
  roberta_tokenizer = AutoTokenizer.from_pretrained('navteca/roberta-base-squad2')
  
  # Get predictions
  nlp = pipeline('question-answering', model=roberta_model, tokenizer=roberta_tokenizer)
  
  result = nlp({
      'question': 'How many people live in Berlin?',
      'context': 'Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.'
  })
  
  print(result)
  
  #{
  #  "answer": "3,520,031"
  #  "end": 36,
  #  "score": 0.96186668,
  #  "start": 27,
  #}
  ```
  