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:
- 2a1fbf31491eaf4c9bb9e39917ce585094224c7901941ce25ab2975a5c6890b3
- Size of remote file:
- 368 kB
- SHA256:
- 93f43720d0bae49068ce3f34f71a6e22b77615ff39097b3afbd713cc09129992
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