JayNightmare/PrERT-CNM-v4-privacybert
PrERT-CNM v4 PrivacyBERT is a Transformers sequence-classification model prepared from the local checkpoint at artifacts\phase-3-privacybert\classifier_checkpoint\privacybert.
Intended Use
Use this model for text classification in the privacy/CNM workflow it was trained for. It is intended for research and application prototyping unless your own validation shows it is suitable for production use.
Labels
usersystemorganization
Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="JayNightmare/PrERT-CNM-v4-privacybert", top_k=None)
scores = classifier("Paste text to classify.")
print(scores)
Training Details
- Base architecture: BERT-compatible sequence classifier
- Source checkpoint:
artifacts\phase-3-privacybert\classifier_checkpoint\privacybert - Training metadata: included when available in the checkpoint folder
Evaluation
Add the final held-out metrics before publishing if they are available. Include dataset split details, label distribution, and any thresholding used by downstream consumers.
Limitations
The model can be sensitive to domain shift, ambiguous language, long inputs, and label definitions that differ from the training data. Review outputs before using them in automated decisions.
Gradio Demo
The companion Space can be prepared from huggingface/space and pointed at this model with the MODEL_ID environment variable.