🤖 text-ranking

jina-reranker-v3

jinaai/jina-reranker-v3

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transformers
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Model Details
Full Model IDjinaai/jina-reranker-v3
Pipeline / Tasktext-ranking
Librarytransformers
Downloads (all-time)1.1M
Likes130
Last Modified3/27/2026
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
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🚀 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.

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📊 Popularity
Downloads1.1M
����� Community Likes130
🛠�� 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.
👋 Need help with code?