Instructions to use CAMeL-Lab/arabart-qalb15-gec-ged-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAMeL-Lab/arabart-qalb15-gec-ged-13 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/arabart-qalb15-gec-ged-13") model = AutoModelForSeq2SeqLM.from_pretrained("CAMeL-Lab/arabart-qalb15-gec-ged-13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CAMeL-Lab/arabart-qalb15-gec-ged-13: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/CAMeL-Lab/arabart-qalb15-gec-ged-13/resolve/main/training_args.bin
- Command line
-
hf download hf://CAMeL-Lab/arabart-qalb15-gec-ged-13/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CAMeL-Lab/arabart-qalb15-gec-ged-13/resolve/main/training_args.bin
3.63 kB
- Xet hash:
- 2571a80719d3c2d0bc8af893930f6759297f7f3100ed3394ec06f22244e38654
- Size of remote file:
- 3.63 kB
- SHA256:
- 5097a21d0f2768c74a30fbcaaa9e2b3fd522d5f21915d3bd3b57cb1df0e4c349
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