Instructions to use Rohan-Kurdekar/Arabic_Bert_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rohan-Kurdekar/Arabic_Bert_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rohan-Kurdekar/Arabic_Bert_Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rohan-Kurdekar/Arabic_Bert_Model") model = AutoModelForMaskedLM.from_pretrained("Rohan-Kurdekar/Arabic_Bert_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Rohan-Kurdekar/Arabic_Bert_Model: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/Rohan-Kurdekar/Arabic_Bert_Model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Rohan-Kurdekar/Arabic_Bert_Model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Rohan-Kurdekar/Arabic_Bert_Model/resolve/main/pytorch_model.bin
334 MB
- Xet hash:
- 758b68e433b07d35931c7ab83170b5dafe20ccd4c25f55a5da958010016fc837
- Size of remote file:
- 334 MB
- SHA256:
- ac3443a25be147f50a5e5a49bb1417f140e302dd883bd4e87c56a8430ea2c01e
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