Instructions to use Qwen/Qwen3-Reranker-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen3-Reranker-8B with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-Reranker-8B") model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-Reranker-8B") - sentence-transformers
How to use Qwen/Qwen3-Reranker-8B with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("Qwen/Qwen3-Reranker-8B") 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
是否可以用于NLI??求回复.
#7
by weiminw - opened
你好, 我看到Qwen3-Reranker支持instruct aware, 我想知道是否可以用这个模型做NLI, 判断前提是否蕴含假设? 比如如下方式写prompt: Instruction: You are an NLI expert. Judge if the premise entails the hypothesis. Query (Premise): 猫坐在垫子上。 Document (Hypothesis): 狗坐在垫子上。reranker会正确的给出分数吗? 或者需要使用Qwen3-8B模型,通过prompt生成特定Token算logits吗?