Text Classification
Transformers
Safetensors
distilbert
privacy
policy-analysis
classification
text-embeddings-inference
Instructions to use skythrone/privacy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skythrone/privacy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="skythrone/privacy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("skythrone/privacy-model") model = AutoModelForSequenceClassification.from_pretrained("skythrone/privacy-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2859ebf3ceb912ffca2ceece41cb5d5666d897e5181a34d834c3cfb06b7069b0
- Size of remote file:
- 536 MB
- SHA256:
- d368c77aa6ed7576fd5e68d25a6942f1fb05542fd803339fc6741214073e4feb
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