Instructions to use GGLab/gec-tr-seq-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GGLab/gec-tr-seq-tagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="GGLab/gec-tr-seq-tagger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("GGLab/gec-tr-seq-tagger") model = AutoModelForTokenClassification.from_pretrained("GGLab/gec-tr-seq-tagger") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6b44c4fbc892484199ae0355171117f315e817041bb397c72eb4dd131808e3b
- Size of remote file:
- 440 MB
- SHA256:
- 7946f2feb1e8fb3b7be28385916b7492e3a9eaf5e19a69f79bba271ae6870a94
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