Instructions to use AimB/mT5-en-kr-natural with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AimB/mT5-en-kr-natural with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AimB/mT5-en-kr-natural") model = AutoModelForSeq2SeqLM.from_pretrained("AimB/mT5-en-kr-natural", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AimB/mT5-en-kr-natural: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/AimB/mT5-en-kr-natural/resolve/a403f947a944c3443ac8f52c3bf633f5cab22135/training_args.bin
- Command line
-
hf download hf://AimB/mT5-en-kr-natural@a403f947a944c3443ac8f52c3bf633f5cab22135/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AimB/mT5-en-kr-natural/resolve/a403f947a944c3443ac8f52c3bf633f5cab22135/training_args.bin
3.12 kB
- Xet hash:
- 1e1399f565b6fd441e37643c5e2556f507981f002b4d6166c439c957f357d0bc
- Size of remote file:
- 3.12 kB
- SHA256:
- 23b9531211c60faae6072accc3327f09936da1d02781c923daf6a43b8cb93d62
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.