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 tokenizer.json from TGiang/mT5: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/TGiang/mT5/resolve/main/tokenizer.json
- Command line
-
hf download hf://TGiang/mT5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TGiang/mT5/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 77453511f83806287e8b0d9fca1fc949d741235a4d6b4f29a08a639d39acebe8
- Size of remote file:
- 16.3 MB
- SHA256:
- 3e866833d80e01bdad22dfa817a1526abd5cbd79fbeba198ed554d628e310d22
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