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- Added model card (f2eecfc0346cf140a1155ea2ab985753fcf20b36)
- Update README.md (a6d098f6271f2b8fad2c4d1a309a2a6e99fdbdd8)
- Update README.md (371054a536db792542756cade10bec4d25eddb2d)


Co-authored-by: Anush Shetty <Anush008@users.noreply.huggingface.co>

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  1. README.md +27 -0
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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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+ ONNX port of [sentence-transformers/clip-ViT-B-32](https://huggingface.co/sentence-transformers/clip-ViT-B-32) 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="Qdrant/clip-ViT-B-32-text")
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+ embeddings = list(model.embed(documents))
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+
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+ # [
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+ # array([1.57889184e-02, -2.21896712e-02, -1.40235685e-02, -2.36918423e-02, ...],
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+ # dtype=float32)
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+ # ]
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+ ```