Instructions to use hf-internal-testing/tiny-random-DebertaForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-DebertaForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-DebertaForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d7513ca0ee3a03acb4c6c82db828bb1333bdaff565db04d09d104c1d6c13268
- Size of remote file:
- 347 kB
- SHA256:
- 92745798643d00ff89f735c500cce4fd17faa10a419189baf82d5c7ce636f1ff
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