Instructions to use KpRT/task-t3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KpRT/task-t3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KpRT/task-t3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KpRT/task-t3") model = AutoModelForTokenClassification.from_pretrained("KpRT/task-t3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66811ec69ccaaa2da59779ffd29683dd6f575cc881a46b7ed6de2ae7e8971ec4
- Size of remote file:
- 5.11 kB
- SHA256:
- 7d820e997d050c2da2f77e2da6b7bc18260932510c59e698c86d2a8237a83355
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