Instructions to use KpRT/task-t1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KpRT/task-t1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KpRT/task-t1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KpRT/task-t1") model = AutoModelForTokenClassification.from_pretrained("KpRT/task-t1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e87d5a96a4418a102694dee906e06ea73039af95663571938c34c4318bc887c
- Size of remote file:
- 5.11 kB
- SHA256:
- 976cd7bfc6394568a3062d7133e01b6a540ff647dbca23911c1a14ec14858ee9
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