ainize/klue-bert-base-mrc

En Transformers

from transformers import AutoModelForQuestionAnswering, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("ainize/klue-bert-base-mrc")
model = AutoModelForQuestionAnswering.from_pretrained("ainize/klue-bert-base-mrc")

context = "tu contexto"
question = "tu pregunta"

encodings = tokenizer(context, question, max_length=512, truncation=True, padding="max_length", return_token_type_ids=False)
encodings = {key: torch.tensor([val]) for key, val in encodings.items()}

input_ids = encodings["input_ids"]
attention_mask = encodings["attention_mask"]

pred = model(input_ids, attention_mask=attention_mask)

start_logits, end_logits = pred.start_logits, pred.end_logits

token_start_index, token_end_index = start_logits.argmax(dim=-1), end_logits.argmax(dim=-1)

pred_ids = input_ids[0][token_start_index: token_end_index + 1]

prediction = tokenizer.decode(pred_ids)