Instructions to use Evuv/mt5-small-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Evuv/mt5-small-torch with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Evuv/mt5-small-torch") model = AutoModelForSeq2SeqLM.from_pretrained("Evuv/mt5-small-torch") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c002d43daac2cff8ed238836274d14498980e85c24cfd4076159b27131e91e77
- Size of remote file:
- 4.31 MB
- SHA256:
- ef78f86560d809067d12bac6c09f19a462cb3af3f54d2b8acbba26e1433125d6
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