Model Details
Full Model IDmixedbread-ai/mxbai-embed-large-v1
Pipeline / Taskfeature-extraction
Librarysentence-transformers
Downloads (all-time)4.3M
Likes785
Last Modified1/23/2026
Author / Orgmixedbread-ai
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="mixedbread-ai/mxbai-embed-large-v1")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
sentence-transformersonnxsafetensorsopenvinoggufbertfeature-extractionmtebtransformers.jstransformersenarxiv:2309.12871license:apache-2.0model-indextext-embeddings-inferenceendpoints_compatibleregion:us
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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
⬇ Downloads4.3M
❤️ Community Likes785
🛠️ 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.