Instructions to use sultan/ArabicTransformer-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sultan/ArabicTransformer-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sultan/ArabicTransformer-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sultan/ArabicTransformer-small") model = AutoModel.from_pretrained("sultan/ArabicTransformer-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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ArabicTransformer small model (B4-4-4 with decoder)
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This model was pre-trained on 44GB of Arabic corpora using [Funnel Transformer with ELECTRA objective](https://arxiv.org/abs/2006.03236). This model is faster than ELECTRA-base archeicture while having same number of parameters. We will update you with more details about the model and our accepted paper later.
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