Instructions to use aubmindlab/bert-base-arabert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aubmindlab/bert-base-arabert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aubmindlab/bert-base-arabert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aubmindlab/bert-base-arabert") model = AutoModelForMaskedLM.from_pretrained("aubmindlab/bert-base-arabert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from aubmindlab/bert-base-arabert: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/aubmindlab/bert-base-arabert/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://aubmindlab/bert-base-arabert/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/aubmindlab/bert-base-arabert/resolve/main/flax_model.msgpack
541 MB
- Xet hash:
- 4b8c62fc93fe3cbd9b6efe7206ff8928d9fef6a483fe1bb14efe3c9681e6da21
- Size of remote file:
- 541 MB
- SHA256:
- c24856665099e9bf4f760178c8ca06f1f8e3a0a0b1154ddea3436e9ac20f356a
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