metadata

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.

Training Data

The models have been trained on the SQuAD 2.0 dataset.

It can be used for question answering task.

Usage and Performance

The trained model can be used like this:

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,
#}