Instructions to use jaimin/arabic-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaimin/arabic-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jaimin/arabic-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jaimin/arabic-bert") model = AutoModelForSequenceClassification.from_pretrained("jaimin/arabic-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jaimin/arabic-bert: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/jaimin/arabic-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jaimin/arabic-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jaimin/arabic-bert/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 196554f41ea8eca230f4120feace21dc9e3659f120e6e8b0975b117e3d6e191d
- Size of remote file:
- 443 MB
- SHA256:
- 1fd6ffcaaf98677b2317f700b4be4e0b33f3fbc577a66161409cd5b1679f1d84
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