Model Details
Full Model IDintfloat/multilingual-e5-large
Pipeline / Taskfeature-extraction
Librarysentence-transformers
Downloads (all-time)6.2M
Likes1.2K
Last Modified4/2/2026
Author / Orgintfloat
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("feature-extraction", model="intfloat/multilingual-e5-large")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
sentence-transformerspytorchonnxsafetensorsopenvinoxlm-robertamtebSentence Transformerssentence-similarityfeature-extractionmultilingualafamarasazbebgbnbrbscacscydadeeleneoes
More feature-extraction 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: feature-extraction
This model is designed for the feature-extraction task. Explore more models for this use case.
All feature-extraction Models →📊 Popularity
⬇ Downloads6.2M
❤️ Community Likes1.2K
🛠️ 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.