Fill-Mask
Transformers
PyTorch
TensorFlow
JAX
Arabic
bert
Arabic BERT
MSA
Twitter
Masked Langauge Model
Instructions to use UBC-NLP/MARBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/MARBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="UBC-NLP/MARBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/MARBERT") model = AutoModelForMaskedLM.from_pretrained("UBC-NLP/MARBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5eab7d5e5eb4c28a79f981a2a49e7e293b6a8bfc1e0a43111e62b3eb9650b820
- Size of remote file:
- 654 MB
- SHA256:
- 801862ace5fc9e6b135b19476dbda5c7de1e8673b5b9d55db08d79e2c30b9dca
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