Instructions to use universalner/uner_eng_ewt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_eng_ewt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_eng_ewt")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_eng_ewt") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_eng_ewt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a2b007a247abf8d265baabb7dca6608e877a9a951baadbaab96ad84c1d4497a
- Size of remote file:
- 2.24 GB
- SHA256:
- 659823b85a8c85d47642d69ba17cd02fac8d38f1dd64e7ad9a674ddac9a88e74
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.