Model Details
Full Model IDjinaai/jina-reranker-v3
Pipeline / Tasktext-ranking
Librarytransformers
Downloads (all-time)853.5K
Likes155
Last Modified8/10/2026
Author / Orgjinaai
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-ranking", model="jinaai/jina-reranker-v3")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsqwen3feature-extractionrerankertext-rankingcustom_codemultilingualarxiv:2509.25085base_model:Qwen/Qwen3-0.6Bbase_model:finetune:Qwen/Qwen3-0.6Blicense:cc-by-nc-4.0region:eu
More text-ranking Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: text-ranking
This model is designed for the text-ranking task. Explore more models for this use case.
All text-ranking Models →📊 Popularity
⬇ Downloads853.5K
❤️ Community Likes155
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.