言語から画像、オープンウェイトからAPIまで。能力と実際の費用を比較。
次のアイデアに合うAIを見つけましょう。
**OpenMed-PII-German-BioClinicalModern-Base-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-BioClinicalModern-Large-395M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
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。
**OpenMed-PII-German-BiomedBERT-Large-340M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-BiomedELECTRA-Base-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-BiomedELECTRA-Large-335M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-ClinicalBGE-Large-335M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-ClinicalBGE-568M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-ClinicalLongformer-149M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-ClinicDischarge-110M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-SnowflakeMed-Large-568M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-SuperClinical-Base-184M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
**OpenMed-PII-German-SuperClinical-Large-434M-v1** is a transformer-based token classification model fine-tuned for **Personally Identifiable Information (PII) detection in German text**. This model identifies and classifies **54 types of sensitive information** including names, addresses, social security numbers, medical record numbers, and more.
翻訳待ち・原文を表示
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。
**OpenMed-PII-Italian-BioClinicalModern-Base-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.
翻訳待ち・原文を表示
**OpenMed-PII-Italian-BioClinicalModern-Large-395M-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.
翻訳待ち・原文を表示
**OpenMed-PII-Italian-BiomedBERT-Base-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.
翻訳待ち・原文を表示
**OpenMed-PII-Italian-BiomedBERT-Large-340M-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.
翻訳待ち・原文を表示
**OpenMed-PII-Italian-BiomedELECTRA-Base-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.
翻訳待ち・原文を表示
**OpenMed-PII-Italian-BiomedELECTRA-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.
翻訳待ち・原文を表示
**OpenMed-PII-Italian-ClinicalBGE-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. - **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)
翻訳待ち・原文を表示
**OpenMed-PII-Italian-ClinicalBGE-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.
翻訳待ち・原文を表示
提供元・分類・入出力の条件を変更してください。新しいモデルを随時追加しています。
月間トークン数を調整してAPI費用を比較。
収集済みの比較可能な100万トークン当たり米ドル料金です。キャッシュ割引、段階料金、追加推論出力、税金は含みません。最新料金は出典で確認してください。
入力・出力・キャッシュ料金を分け、同じ用途と使用量で総費用を比較します。画像・音声・動画は枚数、時間、解像度で課金される場合があります。
必ずしもそうではありません。バージョンごとのライセンス、商用制限、ポリシーを確認してください。自前運用には計算資源と保守費用も必要です。
順位はテスト、バージョン、評価方法によります。実際の業務データで精度、遅延、安定性、費用を比較してください。
