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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Trained on syssec-utd/segmentation-py36-pylingual-v1-tokenized using syssec-utd/py36-pylingual-v1-mlm
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Model save
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Training in progress, epoch 2
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Training in progress, epoch 1
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initial commit
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