plm_qa

roberta-base for QA finetuned over community safety domain data

We fine-tuned the roBERTa-based model (https://huggingface.co/deepset/roberta-base-squad2) over LiveSafe community safety dialogue data for event argument extraction with the objective of question-answering.

Using model in Transformers

from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
model_name = "yirenl2/plm_qa"
# a) Get predictions
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
QA_input = {
    'question': 'What is the location of the incident?',
    'context': 'I was attacked by someone in front of the bus station.'
}
res = nlp(QA_input)
# b) Load model & tokenizer
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)