Instructions to use privacy-tech-lab/MultitaskBaseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/MultitaskBaseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/MultitaskBaseModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/MultitaskBaseModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/MultitaskBaseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c8df0c1791fb64d83c1f1a61a0037eb023c4ee995d1aadea7ceb6972326bd05
- Size of remote file:
- 438 MB
- SHA256:
- 63476c555178eba1767ceae22152906e90dbbad39535fa95d49e12f2fced85d8
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