Instructions to use sultan/ArabicT5-Large_Ar-En with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sultan/ArabicT5-Large_Ar-En with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sultan/ArabicT5-Large_Ar-En") model = AutoModelForSeq2SeqLM.from_pretrained("sultan/ArabicT5-Large_Ar-En", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from sultan/ArabicT5-Large_Ar-En: direct link, hf CLI and curl.
- Browser
- Download file 1.16 GB
-
https://huggingface.co/sultan/ArabicT5-Large_Ar-En/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://sultan/ArabicT5-Large_Ar-En/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/sultan/ArabicT5-Large_Ar-En/resolve/main/flax_model.msgpack
1.16 GB
- Xet hash:
- db28e320c79d3d7ac8f7d915af33c4d523fecdf78a7990cc80159f6ad3270186
- Size of remote file:
- 1.16 GB
- SHA256:
- 54e0db906d01b1113af22a07ac810ee7d6992d80c93e6fb19b7e49989670197e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.