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

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  1. README.md +37 -3
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ pipeline_tag: sentence-similarity
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+ ---
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+ ONNX port of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) adjusted to return attention weights.
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+
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+ This model is intended to be used for [BM42 searches](https://qdrant.tech/articles/bm42/).
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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 SparseTextEmbedding
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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 = SparseTextEmbedding(model_name="Qdrant/bm42-all-minilm-l6-v2-attentions")
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+ embeddings = list(model.embed(documents))
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+
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+ # [
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+ # SparseEmbedding(values=array([0.26399775, 0.24662513, 0.47077307]),
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+ # indices=array([1881538586, 150760872, 1932363795])),
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+ # SparseEmbedding(values=array(
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+ # [0.38320042, 0.25453135, 0.18017513, 0.30432631, 0.1373556]),
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+ # indices=array([
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+ # 733618285, 1849833631, 1008800696, 2090661150,
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+ # 1117393019
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+ # ]))
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+ # ]
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+
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+ ```