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

Name: bge-large-en-v1.5-onnx
Availability: InStock

text-embeddings-inference

endpoints_compatible

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ONNX port of BAAI/bge-large-en-v1.5 for text classification and similarity searches.

Usage

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...])
# ]

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

Usage

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