Text Classification
Transformers
Safetensors
English
bert
BERT
HIPAA
PHI
LLM
sensitive data
classification
healthcare
mHealth Application
cybersecurity
database
column name classifier
data field classifier
huggingface
text-embeddings-inference
Instructions to use barek2k2/bert_hipaa_sensitive_db_schema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use barek2k2/bert_hipaa_sensitive_db_schema with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="barek2k2/bert_hipaa_sensitive_db_schema", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("barek2k2/bert_hipaa_sensitive_db_schema") model = AutoModelForSequenceClassification.from_pretrained("barek2k2/bert_hipaa_sensitive_db_schema", device_map="auto") - Notebooks
- Google Colab
- Kaggle
readme updated
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README.md
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This research work proposes a novel approach that uses BERT based LLM for identifying sensitive database columns into the database schema in order to avoid PHI HIPAA violation.
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#### Disclaimer
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This LLM model is fine-tuned with synthetic dataset(~
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This research work proposes a novel approach that uses BERT based LLM for identifying sensitive database columns into the database schema in order to avoid PHI HIPAA violation.
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#### Disclaimer
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This LLM model is fine-tuned with synthetic dataset(~5K) and is provided for research and educational purposes only. Always verify compliance before using in production environments.
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