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:
- 3c35b3044d7a8107d6df1fe63f79ffa6d2e0e9c489797e4af589628e62bc3f9d
- Size of remote file:
- 3.64 kB
- SHA256:
- f446502a25a0fb20b4e2593f9b3870b4fd4d0e74e337322d1bb54315a78be118
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