Model Details
Full Model IDAlibaba-NLP/gte-multilingual-base
Pipeline / Tasksentence-similarity
Librarysentence-transformers
Downloads (all-time)2.3M
Likes357
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("sentence-similarity", model="Alibaba-NLP/gte-multilingual-base")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
sentence-transformerssafetensorsnewfeature-extractionmtebtransformersmultilingualsentence-similaritytext-embeddings-inferencecustom_codeafarazbebgbncacebcscydadeeleneseteufafifr
More sentence-similarity Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: sentence-similarity
This model is designed for the sentence-similarity task. Explore more models for this use case.
All sentence-similarity Models →📊 Popularity
⬇ Downloads2.3M
❤️ Community Likes357
🛠️ 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.