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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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This model is intended to be used for [BM42 searches](https://qdrant.tech/articles/bm42/). |
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### Usage |
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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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```py |
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from fastembed import SparseTextEmbedding |
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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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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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# 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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``` |
