from sentence_transformers import CrossEncoder

model = CrossEncoder("cross-encoder/nli-deberta-v3-small")

pairs = [
    # 1. Clear entailment
    ["A man is playing soccer.", "A man is playing a sport."],
    # 2. Clear contradiction
    ["A man is playing soccer.", "A man is sleeping."],
    # 3. Clear neutral
    ["A man is playing soccer.", "A man is wearing a red shirt."]
]

scores = model.predict(pairs, apply_softmax=True)
for pair, score in zip(pairs, scores):
    print(f"Pair: {pair}")
    print(f"Scores: [0]={score[0]:.4f}, [1]={score[1]:.4f}, [2]={score[2]:.4f}")