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:
- 847276f575d60f75b7279df490b9cb3cb581d5262c911daad3efb49fc77b5d19
- Size of remote file:
- 8.02 MB
- SHA256:
- 2429f8cfffb2e1ea1bc7ba074ac3c18d023a7742e5cd7149adc649c6ff152069
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