Instructions to use DunnBC22/xlnet-base-cased-finetuned-WikiNeural-PoS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/xlnet-base-cased-finetuned-WikiNeural-PoS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DunnBC22/xlnet-base-cased-finetuned-WikiNeural-PoS")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DunnBC22/xlnet-base-cased-finetuned-WikiNeural-PoS") model = AutoModelForTokenClassification.from_pretrained("DunnBC22/xlnet-base-cased-finetuned-WikiNeural-PoS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 941f874076619dc88b7675dcf4ec3bac705bb753a729940f0365a8bdd2be7e08
- Size of remote file:
- 6.15 kB
- SHA256:
- 6053b9c00923b91be8d39f3ef933e215dc1bbc51aaf5fbbc42da4420d8134688
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