Model reference · open weights
bge-large-en-onnx is an open-weight embedding model from Qdrant.
Summary of the Qdrant/bge-large-en-v1.5-onnx model card, 2026-10-01
What it is
| Released by | Qdrant |
|---|---|
| Released | 2024-01-16 |
From the model card
ONNX port of BAAI/bge-large-en-v1.5 for text classification and similarity searches.
Here's an example of performing inference using the model with FastEmbed.
from fastembed import TextEmbedding
documents = [
"You should stay, study and sprint.",
"History can only prepare us to be surprised yet again.",
]
model = TextEmbedding(model_name="BAAI/bge-large-en-v1.5")
embeddings = list(model.embed(documents))
# [
# array([1.96449570e-02, 1.60677675e-02, 4.10149433e-02...]),
# array([-1.56669170e-02, -1.66313536e-02, -6.84525725e-03...])
# ]
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.