Instructions to use metga97/Modern-EgyBert-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use metga97/Modern-EgyBert-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="metga97/Modern-EgyBert-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("metga97/Modern-EgyBert-Base") model = AutoModelForMaskedLM.from_pretrained("metga97/Modern-EgyBert-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from metga97/Modern-EgyBert-Base: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/metga97/Modern-EgyBert-Base/resolve/main/training_args.bin
- Command line
-
hf download hf://metga97/Modern-EgyBert-Base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/metga97/Modern-EgyBert-Base/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 5099250c27e45ad4cfd158f76ffd4af89986ccec3c31eea52224c65d6469a7c9
- Size of remote file:
- 5.43 kB
- SHA256:
- 385cb14512331aa22db3d476b4f9b107c87c4b1f3457e4aa35d924b2003b1787
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