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:
- 224f9e8a0a7f7dab67c84d249a18069b7002c1a23817da26b7b7d9c8974e04b9
- Size of remote file:
- 3.06 kB
- SHA256:
- 01f6573a4e19132bd356a85e4c60cab4497d1c46e1ec115f92c24a0672468d59
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