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")# 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
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University of West Florida
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📧 hsevil@uwf.edu
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Dr. Guillermo Francia III
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Director, Research and Innovation,
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Center for Cybersecurity,
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University of West Florida
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📧 gfranciaiii@uwf.edu
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Dr. Hossain Shahriar
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Associate Director and Professor, Center for Cybersecurity,
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University of West Florida
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📧 hshahriar@uwf.edu
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University of West Florida
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📧 hsevil@uwf.edu
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**Supervisors:**
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Dr. Guillermo Francia III
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Director, Research and Innovation,
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Center for Cybersecurity,
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University of West Florida
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📧 gfranciaiii@uwf.edu
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Dr. Hossain Shahriar
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Associate Director and Professor, Center for Cybersecurity,
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University of West Florida
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📧 hshahriar@uwf.edu
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Dr. Sheikh Iqbal Ahamed
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Wehr Professor and Founding Chair of Computer Science Department at Marquette University,
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Marquette University
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📧 sheikh.ahamed@marquette.edu
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