Instructions to use BananaFish45/gdpr_personal_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BananaFish45/gdpr_personal_data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BananaFish45/gdpr_personal_data")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BananaFish45/gdpr_personal_data") model = AutoModelForSequenceClassification.from_pretrained("BananaFish45/gdpr_personal_data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 380 Bytes
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license: unknown
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This model basically does check for any personal data in documents what constitutes as personal data is the following:
personal_data_labels = [
"name", "surname", "initials", "date_of_birth", "address", "email_address",
"phone_number", "fax_number", "national_identification_number", "passport_number",
"social_security_number", "tax_number"
] |