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**OpenMed-PII-BiomedELECTRA-Base-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection** in text. This model identifies and classifies **54 types of sensitive information** including names, addresses, SSNs, medical record numbers, and more. ⚠️ **Important**: This model is intended as an **assistive tool**, not a replacement for human review.
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View details ↗**OpenMed-PII-ClinicalBGE-Large-335M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection** in text. This model identifies and classifies **54 types of sensitive information** including names, addresses, SSNs, medical record numbers, and more. ⚠️ **Important**: This model is intended as an **assistive tool**, not a replacement for human review.
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View details ↗**A 109M BERT model for detecting personal and clinical identifiers in English clinical and biomedical text.** Runs locally after download on Python CPU, in the browser, and on Android. OpenMed selects the CPU-oriented INT8 graph by default and returns labels, confidence scores, exact character offsets, and source text. All graphs use opset 18, dynamic batch and sequence axes, stable tensor names, and source-text offset metadata.
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View details ↗**OpenMed-PII-ClinicalE5-Small-33M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection** in text. This model identifies and classifies **54 types of sensitive information** including names, addresses, SSNs, medical record numbers, and more. ⚠️ **Important**: This model is intended as an **assistive tool**, not a replacement for human review.
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View details ↗**OpenMed-PII-ClinicalLongformer-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection** in text. This model identifies and classifies **54 types of sensitive information** including names, addresses, SSNs, medical record numbers, and more. - **High Accuracy**: Achieves strong F1 scores across diverse PII categories - **Comprehensive Coverage**: Detects 50+ entity types spanning personal, financial, medical, and contact information - **Privacy-Focused**: Designed for de-identification and compliance with HIPAA, GDPR, and other privacy regulations - **Production-Ready**: Optimized for real-world text processing pipelines These entity types have lower performance and may benefit from additional post-processing:
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View details ↗**OpenMed-PII-ClinicDischarge-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection** in text. This model identifies and classifies **54 types of sensitive information** including names, addresses, SSNs, medical record numbers, and more. ⚠️ **Important**: This model is intended as an **assistive tool**, not a replacement for human review.
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View details ↗**OpenMed-PII-EuroMed-210M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection** in text. This model identifies and classifies **54 types of sensitive information** including names, addresses, SSNs, medical record numbers, and more. ⚠️ **Important**: This model is intended as an **assistive tool**, not a replacement for human review.
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View details ↗**OpenMed-PII-French-BioClinicalBERT-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-BioClinicalModern-Base-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-BioClinicalModern-Large-395M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-BiomedBERT-Base-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-BiomedBERT-Large-340M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-BiomedELECTRA-Base-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-BiomedELECTRA-Large-335M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-ClinicalBGE-Large-335M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-ClinicalBGE-568M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-ClinicalLongformer-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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View details ↗**OpenMed-PII-French-ClinicDischarge-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in French text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
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