Instructions to use fcfrank10/deberta-cx-01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fcfrank10/deberta-cx-01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fcfrank10/deberta-cx-01", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fcfrank10/deberta-cx-01") model = AutoModelForTokenClassification.from_pretrained("fcfrank10/deberta-cx-01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95d2d3dbb2995af569c91ef97bbb89446a77a6f44e65b3c30eedf8d4f084a7a2
- Size of remote file:
- 4.6 kB
- SHA256:
- 6459a4a12a5ddd25c6a925ade04a0190689f7ba2e71d3893fdd356f2ecde2b71
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