Instructions to use TGiang/mT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TGiang/mT5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("TGiang/mT5") model = AutoModelForSeq2SeqLM.from_pretrained("TGiang/mT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from TGiang/mT5: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/TGiang/mT5/resolve/main/training_args.bin
- Command line
-
hf download hf://TGiang/mT5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TGiang/mT5/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- ede74c50e2174938acc826cdd5e6d71fac70dc8b4dec4d39170da0661c39ccaa
- Size of remote file:
- 3.58 kB
- SHA256:
- 49aa7c8a57d3b4bf579255e5c093bfc548fa6a69176cb6b83f33ab92b46b6b06
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