Instructions to use RUPunct/RUPunct_big with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RUPunct/RUPunct_big with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RUPunct/RUPunct_big")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RUPunct/RUPunct_big") model = AutoModelForTokenClassification.from_pretrained("RUPunct/RUPunct_big") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b098045f982890c4051efd6db9f37d75463c23f0cf195e1a25e44afe77534ba
- Size of remote file:
- 711 MB
- SHA256:
- 7fb3d90660563f7206e8135b15cecea7867227844ee0381aa8b10b383ebe6e03
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.