Instructions to use AfnanTS/AraBERT-EngData with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AfnanTS/AraBERT-EngData with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AfnanTS/AraBERT-EngData")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AfnanTS/AraBERT-EngData") model = AutoModelForMaskedLM.from_pretrained("AfnanTS/AraBERT-EngData", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AfnanTS/AraBERT-EngData: direct link, hf CLI and curl.
- Browser
- Download file 4.02 kB
-
https://huggingface.co/AfnanTS/AraBERT-EngData/resolve/main/training_args.bin
- Command line
-
hf download hf://AfnanTS/AraBERT-EngData/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AfnanTS/AraBERT-EngData/resolve/main/training_args.bin
4.02 kB
- Xet hash:
- 28ac080d4d98c1337a07461ff5ed34a5004fd930340eb86c1f79df05f5380072
- Size of remote file:
- 4.02 kB
- SHA256:
- 7dc6d2903386d9ef7ac9072c68f5f528859039f19ab8ef32f0dbb4dd3a352aae
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