Shobhank-iiitdwd/bert-large-uncased-squad2-QA

bert-large-uncased-whole-word-masking-squad2

This is a berta-large model, fine-tuned using the SQuAD2.0 dataset for the task of question answering.

Overview

Language model: bert-large
Language: English
Downstream-task: Extractive QA
Training data: SQuAD 2.0
Eval data: SQuAD 2.0

Usage

In Transformers

from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline

model_name = "Shobhank-iiitdwd/bert-large-uncased-squad2-QA"

# a) Get predictions
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
QA_input = {
    'question': 'Why is model conversion important?',
    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
}
res = nlp(QA_input)

# b) Load model & tokenizer
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)