Instructions to use privacy-tech-lab/ZipBaseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/ZipBaseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/ZipBaseModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/ZipBaseModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/ZipBaseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e690d77b1951789140d64926df9b78c443093b8c14491dada9d9079b8308d510
- Size of remote file:
- 438 MB
- SHA256:
- 3c97981d9d51f9e6ba1d3d86a6be05b0a0c7024ca11e20e37ccc6e1a7cf47f40
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