Fill-Mask
Transformers
PyTorch
xlm-roberta
Dialectal Arabic
Arabic
sequence labeling
Named entity recognition
Part-of-speech tagging
Zero-shot transfer learning
bert
Instructions to use 3ebdola/Dialectal-Arabic-XLM-R-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3ebdola/Dialectal-Arabic-XLM-R-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="3ebdola/Dialectal-Arabic-XLM-R-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("3ebdola/Dialectal-Arabic-XLM-R-Base") model = AutoModelForMaskedLM.from_pretrained("3ebdola/Dialectal-Arabic-XLM-R-Base") - Notebooks
- Google Colab
- Kaggle
Commit History
Update README.md 330dea7
Abdellah EL MEKKI commited on
Update README.md e14a9e0
Abdellah EL MEKKI commited on
Update README.md 1f87701
Abdellah EL MEKKI commited on
add tokenizer 9e11364
Abdellah EL MEKKI commited on
add model 0e119a0
Abdellah EL MEKKI commited on
initial commit 99ab2af
Abdellah EL MEKKI commited on