**OpenMed-PII-Italian-ClinicalE5-Base-109M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-ClinicalE5-Large-335M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-ClinicalLongformer-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more. - **Italian-Optimized**: Specifically trained on Italian text for optimal performance - **High Accuracy**: Achieves strong F1 scores across diverse PII categories - **Comprehensive Coverage**: Detects 55+ entity types spanning personal, financial, medical, and contact information - **Privacy-Focused**: Designed for de-identification and compliance with GDPR and other privacy regulations - **Production-Ready**: Optimized for real-world text processing pipelines - **Source**: AI4Privacy PII Masking 400k (Italian subset) - **Format**: BIO-tagged token classification - **Labels**: 109 total (54 entity types × 2 BIO tags + O)
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**OpenMed-PII-Italian-ClinicDischarge-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-FastClinical-Base-82M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-LiteClinical-Base-66M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-mLiteClinical-135M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-SnowflakeMed-Large-568M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-SuperClinical-Base-184M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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**OpenMed-PII-Italian-SuperClinical-Large-434M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Italian 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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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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**OpenMed-PII-mClinicalE5-Large-560M-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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**OpenMed-PII-ModernMed-Base-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. ⚠️ **Important**: This model is intended as an **assistive tool**, not a replacement for human review.
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**OpenMed-PII-ModernMed-Large-395M-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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**OpenMed-PII-mSuperClinical-Base-279M-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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**OpenMed-PII-NomicMed-Large-395M-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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**OpenMed-PII-Portuguese-SnowflakeMed-Large-568M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Portuguese 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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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
基本情報を収録・詳細は順次追加
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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**OpenMed-PII-SnowflakeMed-568M-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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**OpenMed-PII-Spanish-BioClinicalBERT-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Spanish text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more. > **Important — Accent Handling:** This model was trained on text without diacritical marks (accents). For best results, strip accents from your input before inference. Character offsets are preserved, so you can map entities back to the original text. > >
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**OpenMed-PII-Spanish-BioClinicalModern-Base-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Spanish text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more. > **Important — Accent Handling:** This model was trained on text without diacritical marks (accents). For best results, strip accents from your input before inference. Character offsets are preserved, so you can map entities back to the original text. > >
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**OpenMed-PII-Spanish-BioClinicalModern-Large-395M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in Spanish text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more. > **Important — Accent Handling:** This model was trained on text without diacritical marks (accents). For best results, strip accents from your input before inference. Character offsets are preserved, so you can map entities back to the original text. > >
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