Instructions to use aubmindlab/bert-large-arabertv02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aubmindlab/bert-large-arabertv02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aubmindlab/bert-large-arabertv02")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aubmindlab/bert-large-arabertv02") model = AutoModelForMaskedLM.from_pretrained("aubmindlab/bert-large-arabertv02", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from aubmindlab/bert-large-arabertv02: direct link, hf CLI and curl.
- Browser
- Download file 1.48 GB
-
https://huggingface.co/aubmindlab/bert-large-arabertv02/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://aubmindlab/bert-large-arabertv02/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aubmindlab/bert-large-arabertv02/resolve/main/pytorch_model.bin
1.48 GB
- Xet hash:
- 0ffc272d93c65476081cb122911204d5320664b77bcfcdc5b8d820abf80af84c
- Size of remote file:
- 1.48 GB
- SHA256:
- 97b717851c0b6297598c174fbda05a71ba2d0524f545c5e612d5429c28ac17c5
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