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:
- 2984db97345f3f6f4f5e5864648268dd3eeec91c5fb5be168ac95ef52db2ee27
- Size of remote file:
- 3.12 kB
- SHA256:
- 0e2de3e37349b1d1bdd2de0067f128982ede335a7d8bbf29b19ffc6676eb2684
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