Krittapad/xlm-roberta-base-finetune-qa-v2

from transformers import AutoTokenizer, AutoModelForQuestionAnswering

# Cargamos el tokenizador y el modelo

model_name = "Krittapad/xlm-roberta-base-finetune-qa-v2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForQuestionAnswering.from_pretrained(model_name)

# Ejemplos de uso
texts = [
    {"text": "Where do I live?", "context": "My name is Wolfgang and I live in Berlin"},
    {"text": "Where do I live?", "context": "My name is Sarah and I live in London"},
    {"text": "What's my name?", "context": "My name is Clara and I live in Berkeley."},
    {"text": "Which name is also used to describe the Amazon rainforest in English?", "context": "The Amazon rainforest (Portuguese: Floresta Amazônica or Amazônia; Spanish: Selva Amazónica, Amazonía or usually Amazonia; ...
]

for text in texts:
    inputs = tokenizer.encode_plus(text["text"], text["context"], add_special_tokens=True, return_tensors="pt")
    answer_start_scores, answer_end_scores = model(**inputs)