Instructions to use Zappandy/mBERT-rom-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zappandy/mBERT-rom-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Zappandy/mBERT-rom-arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Zappandy/mBERT-rom-arabic") model = AutoModelForMaskedLM.from_pretrained("Zappandy/mBERT-rom-arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 508f774569548f4ae0b1d8ec3fbef5a9ba595713f82ddc13ae92ae994f1cd5f4
- Size of remote file:
- 712 MB
- SHA256:
- a4f277ae7720807405c4fdd79016fd0b3842e8c4527729ac761e9aadffe0b517
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