Instructions to use syssec-utd/py310-pylingual-v1-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py310-pylingual-v1-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py310-pylingual-v1-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py310-pylingual-v1-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py310-pylingual-v1-segmenter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39ef3c5f6b0936c7804b0f206897b1dc2234a85ab526a0424d844652991b557b
- Size of remote file:
- 5.5 kB
- SHA256:
- e04460da269f47b3bf717106d88618c2b070274deac81a16541f3583dcb6f60c
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