Instructions to use cgpeltier-janes/deberta-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cgpeltier-janes/deberta-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cgpeltier-janes/deberta-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cgpeltier-janes/deberta-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("cgpeltier-janes/deberta-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d34f373fb3b09428956d22c8dae6a7755f82d740e219cca8bbc74f6e048f091
- Size of remote file:
- 555 MB
- SHA256:
- d7cd69b1c47e7dc2eca94f7f404fb3ce98f9385f1a02b115f392c3a7b66e5bfd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.