Instructions to use SKNahin/NER_Deberta5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SKNahin/NER_Deberta5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SKNahin/NER_Deberta5")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SKNahin/NER_Deberta5") model = AutoModelForTokenClassification.from_pretrained("SKNahin/NER_Deberta5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef1043c3d126d22b6b1b06e7591b1bce5cacc4835f423948d956ffa8bf150285
- Size of remote file:
- 4.73 kB
- SHA256:
- 1a6acd390963b7f90473377197fa75acd65edf28a34a9d9d2f34f27d14ca5770
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