up

README.md

@@ -49,4 +49,17 @@ with torch.no_grad():
     label_mapping = ['contradiction', 'entailment', 'neutral']
     labels = [label_mapping[score_max] for score_max in scores.argmax(dim=1)]
     print(labels)
-```
+```
+
+## Zero-Shot Classification
+This model can also be used for zero-shot-classification:
+```
+from transformers import pipeline
+
+classifier = pipeline("zero-shot-classification", model='cross-encoder/nli-roberta-base')
+
+sent = "Apple just announced the newest iPhone X"
+candidate_labels = ["technology", "sports", "politics"]
+res = classifier(sent, candidate_labels)
+print(res)
+```