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1from transformers import pipeline
2classifier = pipeline("zero-shot-classification",
3 model="Recognai/zeroshot_selectra_medium")
4
5classifier(
6 "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo",
7 candidate_labels=["cultura", "sociedad", "economia", "salud", "deportes"],
8 hypothesis_template="Este ejemplo es {}."
9)
10"""Output
11{'sequence': 'El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo',
12 'labels': ['sociedad', 'cultura', 'salud', 'economia', 'deportes'],
13 'scores': [0.3711881935596466,
14 0.25650349259376526,
15 0.17355826497077942,
16 0.1641489565372467,
17 0.03460107371211052]}
18"""hypothesis_template parameter is important and should be in Spanish. In the widget on the right, this parameter is set to its default value: "This example is {}.", so different results are expected.| Model | Params | XNLI (acc) | *MLSUM (acc) |
|---|---|---|---|
| zs BETO | 110M | 0.799 | 0.530 |
| zs SELECTRA medium | 41M | 0.807 | 0.589 |
| zs SELECTRA small | 22M | 0.795 | 0.446 |