Token Classification
Transformers
PyTorch
TensorFlow
ONNX
Safetensors
xlm-roberta
punctuation prediction
punctuation
Instructions to use oliverguhr/fullstop-punctuation-multilang-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oliverguhr/fullstop-punctuation-multilang-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oliverguhr/fullstop-punctuation-multilang-large")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("oliverguhr/fullstop-punctuation-multilang-large") model = AutoModelForTokenClassification.from_pretrained("oliverguhr/fullstop-punctuation-multilang-large") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 655357e5a7891dee4cb9191e4a00a3e3456be42fa495e023139bfa6cd43aa845
- Size of remote file:
- 618 kB
- SHA256:
- 8414d4e6e5b8f586030fd0bdec34145a24a8eea7c9b7e19fb836dff73773c618
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.