UPDATE, 15.10.2021: Check out our new zero-shot classifiers, much more lightweight and even outperforming this one: zero-shot SELECTRA small and zero-shot SELECTRA medium .
This model is a fine-tuned version of the spanish BERT model with the Spanish portion of the XNLI dataset. You can have a look at the training script for details of the training.
You can use this model with Hugging Face's zero-shot-classification pipeline :
from transformers import pipeline
classifier = pipeline("zero-shot-classification", 
                       model="Recognai/bert-base-spanish-wwm-cased-xnli")
classifier(
    "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo",
    candidate_labels=["cultura", "sociedad", "economia", "salud", "deportes"],
    hypothesis_template="Este ejemplo es {}."
)
"""output
{'sequence': 'El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo',
 'labels': ['cultura', 'sociedad', 'economia', 'salud', 'deportes'],
 'scores': [0.38897448778152466,
  0.22997373342514038,
  0.1658431738615036,
  0.1205764189362526,
  0.09463217109441757]}
"""
 Accuracy for the test set:
| XNLI-es | |
|---|---|
| bert-base-spanish-wwm-cased-xnli | 79.9% |