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
- Xet hash:
- 89547cf0853edaf97e61aca2cf77f46d3ff51f86e6e6836b1bdc92e444e8f929
- Size of remote file:
- 5.24 kB
- SHA256:
- 13876956a2e3f1bd8274ebcf3ca3531994346aa809549469b3b4c24335252e18
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