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")# 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 tf1_model.tar.gz from aubmindlab/bert-large-arabertv02: direct link, hf CLI and curl.
- Browser
- Download file 1.38 GB
-
https://huggingface.co/aubmindlab/bert-large-arabertv02/resolve/main/tf1_model.tar.gz
- Command line
-
hf download hf://aubmindlab/bert-large-arabertv02/tf1_model.tar.gz
-
curl -L -o tf1_model.tar.gz https://huggingface.co/aubmindlab/bert-large-arabertv02/resolve/main/tf1_model.tar.gz
1.38 GB
- Xet hash:
- 96037d06081952a93f57b4af46fcba5cdb5e0c1605e8ecf42f058c18b32a447c
- Size of remote file:
- 1.38 GB
- SHA256:
- c976cd01797caa61ef48bdb5dbad2c9d166022aad8b3e500c6cd96bf5e4e93bd
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