Instructions to use syssec-utd/py36-pylingual-v1-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py36-pylingual-v1-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py36-pylingual-v1-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py36-pylingual-v1-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py36-pylingual-v1-segmenter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb05a6f1e160b2f04741a5d75d9672eb9cb70cf15b07840f6b6db9d23641a827
- Size of remote file:
- 5.43 kB
- SHA256:
- 71711adcf9c29b12b6f541314c71ba0c2b6aed4ebe8a0e6a2611a957040bd213
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