Instructions to use syssec-utd/py313-pylingual-v1-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py313-pylingual-v1-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py313-pylingual-v1-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py313-pylingual-v1-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py313-pylingual-v1-segmenter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b5b2f28531cd6b97a79b6e5e5ede5cc480c10611b5d70512087bedd7b608f7b
- Size of remote file:
- 5.43 kB
- SHA256:
- 51a0ad05a5b2acd3144621461147e0f715ead407235342d0c6292cd551e3c0ff
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