Instructions to use hf-tiny-model-private/tiny-random-DebertaForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DebertaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-DebertaForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df1a62ef727a8d76f4ece8b81f37b98bfd2bc99fdbe592fbe27dfa77a231e4ab
- Size of remote file:
- 347 kB
- SHA256:
- 7252add2a9aedbe933c6d5b557848b415f8753821900a3be932fde2d82bce06d
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