Is that possible? If so, how can I do that?
Yes that’s possible, like so:
from transformers import BertTokenizer, BertForQuestionAnswering
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForQuestionAnswering.from_pretrained('bert-base-uncased')
context = "Jim Henson was a nice puppet"
questions = ["Who was Jim Henson?", "What is Jim's last name?"]
inputs = tokenizer(questions, [context for _ in range(len(questions))], padding=True, return_tensors='pt')
outputs = model(**inputs)
start_scores = outputs.start_logits
end_scores = outputs.end_logits
We just make several [CLS] question [SEP] context [SEP] [PAD] [PAD] ...
examples, which we forward through the model.
1 Like
Thank you so much!