rajpurkar/squad_v2
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How to use navteca/electra-base-squad2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="navteca/electra-base-squad2") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("navteca/electra-base-squad2")
model = AutoModelForQuestionAnswering.from_pretrained("navteca/electra-base-squad2")This model uses electra-base.
The models have been trained on the SQuAD 2.0 dataset.
It can be used for question answering task.
The trained model can be used like this:
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
# Load model & tokenizer
electra_model = AutoModelForQuestionAnswering.from_pretrained('navteca/electra-base-squad2')
electra_tokenizer = AutoTokenizer.from_pretrained('navteca/electra-base-squad2')
# Get predictions
nlp = pipeline('question-answering', model=electra_model, tokenizer=electra_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": 0.99983448,
# "start": 27,
#}