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 flax_model.msgpack 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/flax_model.msgpack
- Command line
-
hf download hf://Rohan-Kurdekar/Arabic_Bert_Model/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Rohan-Kurdekar/Arabic_Bert_Model/resolve/main/flax_model.msgpack
334 MB
- Xet hash:
- 161339e37943fcd0693076fd4d2e3594e4fb68ea34995b131393a92231260eb4
- Size of remote file:
- 334 MB
- SHA256:
- e05718ddd0d3e3be74dbde6f8e52806a12c2fa82d959773d80034122895408a2
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