Text Ranking
Transformers
Safetensors
sentence-transformers
qwen3_vl
image-text-to-text
multimodal rerank
text rerank
Instructions to use Qwen/Qwen3-VL-Reranker-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen3-VL-Reranker-2B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-Reranker-2B") model = AutoModelForMultimodalLM.from_pretrained("Qwen/Qwen3-VL-Reranker-2B", device_map="auto") - sentence-transformers
How to use Qwen/Qwen3-VL-Reranker-2B with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("Qwen/Qwen3-VL-Reranker-2B") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle
Tom Aarsen commited on
Commit ·
6232aef
1
Parent(s): 023385f
Add unpad_inputs=False
Browse files
sentence_bert_config.json
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@@ -20,6 +20,7 @@
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},
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"module_output_name": "causal_logits",
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"message_format": "structured",
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"processing_kwargs": {
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"chat_template": {
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"chat_template": "reranker",
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},
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"module_output_name": "causal_logits",
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"message_format": "structured",
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"unpad_inputs": false,
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"processing_kwargs": {
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"chat_template": {
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"chat_template": "reranker",
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