Instructions to use syssec-utd/py311-pylingual-v1-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py311-pylingual-v1-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py311-pylingual-v1-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py311-pylingual-v1-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py311-pylingual-v1-segmenter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 480ffa063ab7d8229c0b72c734f6576047f6fb8610241d23285d117f53d84879
- Size of remote file:
- 5.43 kB
- SHA256:
- 0625cec3d44555d9c529f86ec9baa78e84b74b35da050b40e0277505eecae886
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