Instructions to use bashar-talafha/multi-dialect-bert-base-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bashar-talafha/multi-dialect-bert-base-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bashar-talafha/multi-dialect-bert-base-arabic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bashar-talafha/multi-dialect-bert-base-arabic") model = AutoModelForMaskedLM.from_pretrained("bashar-talafha/multi-dialect-bert-base-arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bashar-talafha/multi-dialect-bert-base-arabic: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/bashar-talafha/multi-dialect-bert-base-arabic/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bashar-talafha/multi-dialect-bert-base-arabic/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bashar-talafha/multi-dialect-bert-base-arabic/resolve/main/pytorch_model.bin
445 MB
- Xet hash:
- eadbf6e62a4f3c951c0d0adc35c39ce70092d6a8f03e70b885b3bbe48c5dc87e
- Size of remote file:
- 445 MB
- SHA256:
- 341182414b5693d7eb1f779de1033c3d40f05032f13e3d4ea26c2b84376e7ee4
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