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:
- afae1db3e0e64bc64f39d1923e968da427f8307c68880396a9d06c4a64029a9c
- Size of remote file:
- 438 MB
- SHA256:
- f0a02aa0dc319e0ca5d5660aaad43a8c7948cf04a7533b131957c9ce045bbff0
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