Muthukumaran
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README.md
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@@ -81,6 +81,13 @@ passage_embeddings = model.encode(input_passages)
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print(util.cos_sim(query_embeddings, passage_embeddings))
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```
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## Citation
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If you find this work useful, please cite using the following bibtex citation:
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print(util.cos_sim(query_embeddings, passage_embeddings))
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```
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# Note
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This Sentence Transformer Model is released in support of the training and evaluation of the encoder language model ["Indus"](https://huggingface.co/nasa-impact/nasa-smd-ibm-v0.1).
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Accompanying paper can be found here: https://arxiv.org/abs/2405.10725
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## Citation
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If you find this work useful, please cite using the following bibtex citation:
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