Fill-Mask
Transformers
PyTorch
TensorFlow
JAX
Arabic
bert
Arabic BERT
MSA
Twitter
Masked Langauge Model
Instructions to use UBC-NLP/ARBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/ARBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="UBC-NLP/ARBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/ARBERT") model = AutoModelForMaskedLM.from_pretrained("UBC-NLP/ARBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
elmadany commited on
Commit ·
c92775c
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Parent(s): eadb0a9
Update config
Browse files- config.json +3 -1
config.json
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{
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"
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"attention_probs_dropout_prob": 0.1,
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"directionality": "bidi",
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"gradient_checkpointing": false,
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{
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"architectures": [
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"BertForMaskedLM"
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],
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"attention_probs_dropout_prob": 0.1,
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"directionality": "bidi",
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"gradient_checkpointing": false,
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