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")# pip install -U transformers accelerate # 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
Download checkpoint-1044/optimizer.pt from barek2k2/bert_hipaa_sensitive_db_schema: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/barek2k2/bert_hipaa_sensitive_db_schema/resolve/main/checkpoint-1044/optimizer.pt
- Command line
-
hf download hf://barek2k2/bert_hipaa_sensitive_db_schema/checkpoint-1044/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/barek2k2/bert_hipaa_sensitive_db_schema/resolve/main/checkpoint-1044/optimizer.pt
876 MB
- Xet hash:
- 948378216d62f86e7e3dda5ee8977ac8c35f02687e0ed0b3d94c7ee6d49ef15f
- Size of remote file:
- 876 MB
- SHA256:
- 240d1827088543a51edb1df51f1915a6a2568b8362b898c8a8434b3aeeea9468
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.