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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16264b674d1d179049261634a7bfcbffe541742d34de65af4c5958ea481d48a5
- Size of remote file:
- 5.3 kB
- SHA256:
- 80523e51d2f83e6a2a16fa7702bf64d5d926f0007e6d9e19adf73b1e0359ec1c
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