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:
- 98b5540ceb80b43a685a3053569158da7aecba9231b40eb753281e759a6fd4c5
- Size of remote file:
- 652 MB
- SHA256:
- b6027e3cc4e9e45373bbc9070b8a5f7a91acfff414d7aa0d3f77d1e636f83f59
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