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:
- 151b46046b0a7ed20bda9c9c9f615fce0fd499a58f1d0f1cb87dea0a0a6bf002
- Size of remote file:
- 3.06 kB
- SHA256:
- 5319e1437f038c63bb340369eab935fde9a26b10526a84390a7bd243484b8107
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