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:
- ebac600ec446386791361e19379c44e3b446344184a7e8057d27b702bf762047
- Size of remote file:
- 555 MB
- SHA256:
- a4938f44a186293cdb9c797701010a75760cf50cd9e38cb4ea5cb1cd66c89faf
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