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Added model card (#1)
Browse files- Added model card (a5ce8e1561737d421b217619ee26e802ea07a199)
- Update README.md (78b113ad7c26b4873b432ebfb92c0b071039e075)
Co-authored-by: Anush Shetty <[email protected]>
README.md
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---
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license: apache-2.0
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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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```
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