Instructions to use syssec-utd/py313-pylingual-v3-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py313-pylingual-v3-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py313-pylingual-v3-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py313-pylingual-v3-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py313-pylingual-v3-segmenter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0441e5b0d957aa7f8f98eb02749c2ac8c2f05d3d911eb491e97a286f5aa496d
- Size of remote file:
- 5.27 kB
- SHA256:
- b1640a3249c3254e7b21b98bec31ece7b63d1c03ad90339171c8e6b10016aa2b
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