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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bae4e356954cac37e2315a9f577a6d7ba4f6ea8b4574930bf61bcd9af8f6b78
- Size of remote file:
- 438 MB
- SHA256:
- 246a947a5e4ce36b9e058c1592bba046d39b6ea36ed8eadaaefdd9d712c8fe99
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