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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 662f7aea7d364581acc0246504c644272ac5a9acdc9b157a41b8a65eb00ae4f9
- Size of remote file:
- 1.79 GB
- SHA256:
- eb2ce0d9a53a286fff919daee2700a1ad232488cde15e2f8852cba246834e930
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