Instructions to use AhmedSSoliman/MarianCG-CoNaLa-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AhmedSSoliman/MarianCG-CoNaLa-Large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa-Large") model = AutoModelForSeq2SeqLM.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa-Large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AhmedSSoliman/MarianCG-CoNaLa-Large: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/AhmedSSoliman/MarianCG-CoNaLa-Large/resolve/main/training_args.bin
- Command line
-
hf download hf://AhmedSSoliman/MarianCG-CoNaLa-Large/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AhmedSSoliman/MarianCG-CoNaLa-Large/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- 143d1a8e2ad42376089e4dc73df05bcdeb49b7616becb908ee1f87a79cf32fdc
- Size of remote file:
- 3.18 kB
- SHA256:
- ba1d19a979690d644f43c43f0c5ac2bb8f020a2e184411448c847a0cb70acae2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.