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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 407c494bfe08d4089e684e4350689d9e632e0b70d6a3cf7d7f8c415341ffac1f
- Size of remote file:
- 57.4 MB
- SHA256:
- faa461e2ed2cdcdf1525063fe4fa09b54972b6c8f0817a22380a2cda620bb727
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