Instructions to use frizwankhan/tokenization_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frizwankhan/tokenization_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="frizwankhan/tokenization_model")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("frizwankhan/tokenization_model") model = AutoModelForTokenClassification.from_pretrained("frizwankhan/tokenization_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f8ecf39b133d5872fd14963b9c300def9c78dd953199a87d717b7a310e3de85
- Size of remote file:
- 802 MB
- SHA256:
- 375eda5dab3a2dcc7633af047b908a8362e8cdefed5f6322441bec0ca8089238
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