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
Add label2id and id2label configs
#10 opened 2 months ago
by
kozistr
Working GGUF for llama.cpp (native Windows/Linux, no WSL needed)
🔥 1
#9 opened 3 months ago
by
Voodisss
Howto create a FP8 quant?
#8 opened 5 months ago
by
JochenGebhard
是否可以用于NLI??求回复.
#7 opened 6 months ago
by
weiminw
为什么不能使用chat_template
#6 opened 10 months ago
by
weiminw
Training supported
🚀 2
2
#5 opened 11 months ago
by
russwest404
Add pipeline tag
#3 opened 12 months ago
by
nielsr
Encountered an error while starting the model using VLLM.
3
#2 opened 12 months ago
by
wuht1
Rerank (Score) API
👍 5
2
#1 opened 12 months ago
by
alexhyzheng