Instructions to use wennycooper/token-classification-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wennycooper/token-classification-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wennycooper/token-classification-bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wennycooper/token-classification-bert-base-uncased") model = AutoModelForTokenClassification.from_pretrained("wennycooper/token-classification-bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 825dbb1966efd4dd4ccac5861455b2cf29ad5fed3cd8848cf2a42e021c7a466f
- Size of remote file:
- 436 MB
- SHA256:
- a747c8fb009df5e0b9e446953b4846ed52f0ff88d2076c6f033bf247b8004d75
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