Instructions to use syssec-utd/py314-pylingual-v5-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py314-pylingual-v5-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py314-pylingual-v5-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py314-pylingual-v5-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py314-pylingual-v5-segmenter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3420a085b879281d9813801331a2cea3a38c12cf9a970e37eddb87907c2bf11
- Size of remote file:
- 5.27 kB
- SHA256:
- 63121481ec4bfce6eec5df4d0410b624456b00011cf698c963aa1a9b7e1b0d69
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