Instructions to use dbsamu/deberta-base-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbsamu/deberta-base-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dbsamu/deberta-base-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dbsamu/deberta-base-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("dbsamu/deberta-base-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52dffbb8e83c8ac2053d1b91f3b3ab5cd3f6d66d913e7336106e629b982f1c52
- Size of remote file:
- 2.93 kB
- SHA256:
- 9da5f386726c7ecd70847c1c3b4a24db58931445d707bfc443c9568ae60cef07
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