Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use kktoto/kt_punc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kktoto/kt_punc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kktoto/kt_punc")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kktoto/kt_punc") model = AutoModelForTokenClassification.from_pretrained("kktoto/kt_punc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae0e0ea21bb0ea23faec28b2f93f9625a748c8687d44129b5fffc04c41fb954d
- Size of remote file:
- 3.18 kB
- SHA256:
- 8b67c94bf4b16559ed76f9188b460e6b51b4b6919a8000c0c914527ed7df6513
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