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:
- d5ff991bb43741147ed9f8d4bce8bc8f960d3fe8651ea297b41da9479b93268f
- Size of remote file:
- 3.12 kB
- SHA256:
- 45431349e697fc52b0547d8cdb75dccb4b491c5504ccb3a909150c44f4e15da5
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