Instructions to use RJ3vans/DeBERTaCCVspanTagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJ3vans/DeBERTaCCVspanTagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RJ3vans/DeBERTaCCVspanTagger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RJ3vans/DeBERTaCCVspanTagger") model = AutoModelForTokenClassification.from_pretrained("RJ3vans/DeBERTaCCVspanTagger") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 539a4e71ce49e07aac2c033a378ed5687d776267739df72e6d9d2c246cd696a2
- Size of remote file:
- 735 MB
- SHA256:
- 0e248083f911a57f27cbd7164a92b16a5773de45d866e6949bc0c342637eef5d
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