Instructions to use ydshieh/tiny-random-DebertaV2ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaV2ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ydshieh/tiny-random-DebertaV2ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaV2ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("ydshieh/tiny-random-DebertaV2ForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 934c3d515be12cdcea3afffadfc8e5b105493be7ea67575daf1e7cad9384af96
- Size of remote file:
- 462 kB
- SHA256:
- 79f8a0bfe1634b4a2ffa1740f40001f9d08189d99b6895a885e2463ed201f9de
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