Instructions to use aubmindlab/bert-base-arabertv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aubmindlab/bert-base-arabertv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aubmindlab/bert-base-arabertv2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aubmindlab/bert-base-arabertv2") model = AutoModelForMaskedLM.from_pretrained("aubmindlab/bert-base-arabertv2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from aubmindlab/bert-base-arabertv2: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/aubmindlab/bert-base-arabertv2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://aubmindlab/bert-base-arabertv2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/aubmindlab/bert-base-arabertv2/resolve/main/flax_model.msgpack
541 MB
- Xet hash:
- da912abc15fff88c5b3b2c7568fced72b74927daf7648b04de78d6f9cbef68c0
- Size of remote file:
- 541 MB
- SHA256:
- 7295a5bf0e3fec438eb0ad996240a40dfed769fa3c12636925289f5a3969300e
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