ericRosello/bert-base-uncased-finetuned-squad-frozen-v1

# Uso del modelo
from transformers import BertTokenizer, BertForQuestionAnswering
import torch

# Cargar el tokenizador y el modelo
model_name = 'ericRosello/bert-base-uncased-finetuned-squad-frozen-v1'
tokenizer = BertTokenizer.from_pretrained(model_name)
model = BertForQuestionAnswering.from_pretrained(model_name)

# Ejemplo de entrada
question = 'What is the name of the model?'
context = 'Este modelo es una versión afinada de bert-base-uncased en el conjunto de datos SQuAD.'
inputs = tokenizer(question, context, return_tensors='pt')

# Realizar inferencia
with torch.no_grad():
    outputs = model(**inputs)

start_logits = outputs.start_logits
end_logits = outputs.end_logits

# Obtener la respuesta
all_tokens = tokenizer.convert_ids_to_tokens(inputs['input_ids'][0])
answer = ' '.join(all_tokens[torch.argmax(start_logits): torch.argmax(end_logits)+1])
print('Respuesta:', answer)