Instructions to use privacy-tech-lab/CityBaseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/CityBaseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/CityBaseModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/CityBaseModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/CityBaseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cb97c50a668d88a9ccfce4d191cb49adb79a1e0b9ae074765c2152fb50fb0cb
- Size of remote file:
- 438 MB
- SHA256:
- f440cdd777d16a1f4f9340d5c617871e031b1e83ae57e2d65da7d292c32d994a
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