🤖 text-ranking

gte-multilingual-reranker-base

Alibaba-NLP/gte-multilingual-reranker-base

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Tags
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sentence-transformers
Library
Model Details
Full Model IDAlibaba-NLP/gte-multilingual-reranker-base
Pipeline / Tasktext-ranking
Librarysentence-transformers
Downloads (all-time)181.3K
Likes180
Last Modified7/5/2025
Author / OrgAlibaba-NLP
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="Alibaba-NLP/gte-multilingual-reranker-base")

# Run inference
result = pipe("Your input here")
print(result)
����� Tags
sentence-transformerssafetensorsnewtext-classificationtransformerstext-embeddings-inferencetext-rankingcustom_codeafarazbebgbncacebcscydadeeleneseteufafifrglgu
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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
Downloads181.3K
����� Community Likes180
🛠�� Requirements
  • Install: pip install sentence-transformers
  • Python 3.8+ recommended for Transformers.
  • GPU (CUDA) speeds up inference significantly.
  • Use model.half() for fp16 on limited VRAM.
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