GLiNER
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Order of labels impacts detection confidence scores
I'm using the PII model using the following script:
model = GLiNER.from_pretrained("urchade/gliner_multi_pii-v1")
model.eval()
entities = model.predict_entities(text, labels)
for entity in entities:
print(entity["text"], "=>", entity["label"], "=>", entity["score"] )
If my order of labels changes, I get a different score for the detected entities. Why is this happening?