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:
- c7c3ff167b7d0027b3888634afda11e2fc92aedf4b4a9261bd843074be1e2483
- Size of remote file:
- 3.12 kB
- SHA256:
- f3ee8b24d855275612d07ab2e9a48970a18e9426ae4ec4cd469706da77446167
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