Qwen3-VL-Reranker-2B

pip install sentence_transformers

from sentence_transformers import CrossEncoder

model = CrossEncoder("Qwen/Qwen3-VL-Reranker-2B")

query = "A woman playing with her dog on a beach at sunset."
documents = [
    "A woman shares a joyful moment with her golden retriever on a sun-drenched beach at sunset, as the dog offers its paw in a heartwarming display of companionship and trust.",
    "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
    {
        "text": "A woman shares a joyful moment with her golden retriever on a sun-drenched beach at sunset, as the dog offers its paw in a heartwarming display of companionship and trust.",
        "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
    },
]

prompt = "Retrieve images or text relevant to the user's query."
pairs = [(query, doc) for doc in documents]
scores = model.predict(pairs, prompt=prompt)
print(scores)
# [1.8125, 0.5625, 1.3125]

rankings = model.rank(query, documents, prompt=prompt)
print(rankings)
# [{'corpus_id': 0, 'score': 1.8125}, {'corpus_id': 2, 'score': 1.3125}, {'corpus_id': 1, 'score': 0.5625}]