Instructions to use Qwen/Qwen3-Reranker-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen3-Reranker-4B with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-Reranker-4B") model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-Reranker-4B") - sentence-transformers
How to use Qwen/Qwen3-Reranker-4B with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("Qwen/Qwen3-Reranker-4B") 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
Not able to Reproduce results in MTEB
👍➕ 2
1
#12 opened 30 days ago
by
AyushM6
Add `id2label` and `label2id` configs
#10 opened 2 months ago
by
kozistr
Working GGUF for llama.cpp (native Windows/Linux, no WSL needed)
#9 opened 3 months ago
by
Voodisss
QWEN instruct vs qwen reranker
#8 opened 5 months ago
by
kalle07
Training supported
#7 opened 11 months ago
by
russwest404
qwen3-reranker系列对于相同文本的分数,表现非常差
2
#6 opened 11 months ago
by
bobliu2020
does the tokenizer need to be updated for this model?
1
#5 opened 11 months ago
by
electroglyph
Amazing work! Any plans to release the fine-tuning toolkit for Qwen3-Reranker?
#4 opened 12 months ago
by
wynne-mw
Add pipeline tag and link to paper and project page
#2 opened 12 months ago
by
nielsr
typo report
👀 1
#1 opened 12 months ago
by
wsp