Instructions to use syssec-utd/py315-pylingual-v2-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py315-pylingual-v2-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py315-pylingual-v2-segmenter")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py315-pylingual-v2-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py315-pylingual-v2-segmenter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Trained on syssec-utd/segmentation-py315-pylingual-v2-tokenized using syssec-utd/py315-pylingual-v2-mlm
Verified signature12cc39d -
Model save
Verified signaturef3c8c3e -
Training in progress, epoch 2
Verified signature7d5888d -
Training in progress, epoch 1
Verified signatureca74db0 -
initial commit
Verified signature54b6f2c