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Update README.md

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@@ -70,12 +70,6 @@ entities = detect_entities(model, text, entities={
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  "LAB_VALUE": "Laboratory test result",
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  })
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- # Or even abstract analytical entities
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- entities = detect_entities(model, text, entities={
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- "COMMITMENT": "A promise or obligation",
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- "ASSUMPTION": "An unstated premise or belief",
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- "RISK_FACTOR": "A potential source of risk or uncertainty",
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- })
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  ```
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  This isn't prompt engineering or few-shot learning. The model's bi-encoder architecture natively supports arbitrary entity schemas. Fine-tuning on PII improves precision on those specific types without degrading the zero-shot capability.
 
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  "LAB_VALUE": "Laboratory test result",
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  })
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  ```
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  This isn't prompt engineering or few-shot learning. The model's bi-encoder architecture natively supports arbitrary entity schemas. Fine-tuning on PII improves precision on those specific types without degrading the zero-shot capability.