Instructions to use privacy-tech-lab/MultitaskDistilledModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/MultitaskDistilledModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/MultitaskDistilledModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/MultitaskDistilledModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/MultitaskDistilledModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ade951616b0d3ad1109df7a36dfaee700548a6f36a3eedfd1f30de4dece178b9
- Size of remote file:
- 3.12 kB
- SHA256:
- 81b3db6783d7c8873d5e5c9d0bc0ec32a7cfa4b60f7a1b244fc90354cddfd4cf
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