Instructions to use privacy-tech-lab/RegionDistilledModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/RegionDistilledModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/RegionDistilledModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/RegionDistilledModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/RegionDistilledModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbcea3a26023f5be75b1bf25626c46828108f85fd4a8bb1bf11abb3767e55e48
- Size of remote file:
- 57.4 MB
- SHA256:
- 1efc3d0b06a05adad53cc0749eb7ec4fedd7164139d02e14738b091b08ea71ef
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