Instructions to use privacy-tech-lab/ZipModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/ZipModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/ZipModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/ZipModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/ZipModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3e218f8039d3b437e253438a616ae41155dd58c98799f86e4ec4ad36dc11de5
- Size of remote file:
- 57.4 MB
- SHA256:
- fbc779b6ab564f614f73cfa057abeda7e93b2d934d02a26e16f60b0c5ac02db7
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