Instructions to use syssec-utd/py39-pylingual-v1-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py39-pylingual-v1-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py39-pylingual-v1-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py39-pylingual-v1-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py39-pylingual-v1-segmenter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d2eed8506804313b4a1067c453bd2f1685776ff4a6e858cb3cb45424e77d56c
- Size of remote file:
- 5.43 kB
- SHA256:
- 84906cb958df6d58161d28bc8b147f0bf7f79861372257179a7a9b190e690ddd
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