Qdrant/bge-large-en-v1.5-onnx

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...])
# ]