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:
- 6effdf4a9e1fde98cb2da23a7802b9c132944e7185ba6512f98fb6d4e78146fa
- Size of remote file:
- 467 MB
- SHA256:
- b7b44657f66f67313c4502238c7a42d3b1152339a29efcfcf99af7e61fcad74f
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