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Added a model card

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+ ---
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+ license: apache-2.0
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+ pipeline_tag: sentence-similarity
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+ ---
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+
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+ Quantized ONNX port of [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) for text classification and similarity searches.
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+
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+ ### Usage
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+
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+ Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
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+
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+ ```py
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+ from fastembed import TextEmbedding
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+
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+ documents = [
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+ "You should stay, study and sprint.",
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+ "History can only prepare us to be surprised yet again.",
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+ ]
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+
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+ model = TextEmbedding(model_name="BAAI/bge-base-en-v1.5")
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+ embeddings = list(model.embed(documents))
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+
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+ # [
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+ # array([
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+ # 0.00611658, 0.00068912, -0.0203846, ..., -0.01751488, -0.01174267,
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+ # 0.01463472
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+ # ],
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+ # dtype=float32),
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+ # array([
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+ # 0.00173448, -0.00329958, 0.01557874, ..., -0.01473586, 0.0281806,
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+ # -0.00448205
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+ # ],
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+ # dtype=float32)
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+ # ]
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+ ```