Instructions to use sileod/deberta-v3-base-tasksource-adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sileod/deberta-v3-base-tasksource-adapters with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sileod/deberta-v3-base-tasksource-adapters")# Load model directly from transformers import AutoTokenizer, Adapter tokenizer = AutoTokenizer.from_pretrained("sileod/deberta-v3-base-tasksource-adapters") model = Adapter.from_pretrained("sileod/deberta-v3-base-tasksource-adapters", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 912c0d951705b15c596119650d7c6a9feef3f472759b74128c2d03285a557b22
- Size of remote file:
- 8 MB
- SHA256:
- 784f636e93636cfa751b58ff1797cf777b92788e0723012d3b8d52404b51e5bd
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