Instructions to use hf-internal-testing/tiny-random-DebertaV2ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaV2ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-DebertaV2ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bbf3df4a657f9f115eb27976b159e8b1840e6a484c15d95bb2a76e2aa646527
- Size of remote file:
- 16.7 MB
- SHA256:
- 0dda6afec2ac57a7d827a96bdc43f0f2cb560036b483503ee564ffc96f8f42d9
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