Instructions to use moussaKam/AraBART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moussaKam/AraBART with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="moussaKam/AraBART")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("moussaKam/AraBART") model = AutoModel.from_pretrained("moussaKam/AraBART", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4e4b6208e0f4cc1cd1873204fa17a780068fb132fffc71dd80d22a0829ac3e6
- Size of remote file:
- 557 MB
- SHA256:
- 2c7baf1b29372a022b3b80a6b4fb3e14a47595da56fb2008d19f16cd74394ba9
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