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README.md
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---
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license:
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tags:
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- setfit
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- sentence-transformers
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- text-classification
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pipeline_tag: text-classification
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---
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# test_depres
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("test_depres")
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# Run inference
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preds = model(["
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```
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## BibTeX entry and citation info
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copyright = {Creative Commons Attribution 4.0 International}
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}
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```
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---
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license: mit
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tags:
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- setfit
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- sentence-transformers
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- text-classification
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pipeline_tag: text-classification
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language:
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- multilingual
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---
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---
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# test_depres
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("test_depres")
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dict ={0:"positive", 1:"negative"}
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# Run inference
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preds = model(["What happened to me? I don't know what to do, where to go! Can anyone help me?"])
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dict.get(str(list(preds))[1:-1])
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```
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## BibTeX entry and citation info
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copyright = {Creative Commons Attribution 4.0 International}
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}
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```
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## Citing & Authors
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```
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@misc{Uaritm,
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title={SetFit: Classification of medical texts},
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author={Vitaliy Ostashko},
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year={2022},
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url={https://esemi.org}
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}
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<!--- Describe where people can find more information -->
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