Instructions to use privacy-tech-lab/CityModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/CityModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/CityModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/CityModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/CityModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbb9a1fa233dcb1a32e02aedf51c47c294388c0ea5b68a55e73adb4d1060cb0a
- Size of remote file:
- 57.4 MB
- SHA256:
- 4bc55782051767d846703d77aaeb2777e1dc3e3e80897a02cb3d45db9dc81dec
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