Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
xlm-roberta
punctuation prediction
punctuation
Instructions to use oliverguhr/fullstop-punctuation-multilingual-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oliverguhr/fullstop-punctuation-multilingual-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oliverguhr/fullstop-punctuation-multilingual-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("oliverguhr/fullstop-punctuation-multilingual-base") model = AutoModelForTokenClassification.from_pretrained("oliverguhr/fullstop-punctuation-multilingual-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from oliverguhr/fullstop-punctuation-multilingual-base: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/oliverguhr/fullstop-punctuation-multilingual-base/resolve/main/training_args.bin
- Command line
-
hf download hf://oliverguhr/fullstop-punctuation-multilingual-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/oliverguhr/fullstop-punctuation-multilingual-base/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- c15f9ed4bf08cf8bb4a5767cc6de222870bf73816eb1958bc05e3e9f735cc7ea
- Size of remote file:
- 3.06 kB
- SHA256:
- ec83374399e06bb1aa7aa5a0add1d9b12fc14132e18697c121256e860e247684
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.