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:
- cff74e35676c23bc225bca25d20f1646fea626b37a0da71ceede27cf23d499c5
- Size of remote file:
- 443 kB
- SHA256:
- 0910ea2da7af54684fe21ce0130533d1462c3374d68261b07babe079f62b74ab
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