Instructions to use transZ/ViT5-repara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transZ/ViT5-repara with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("transZ/ViT5-repara") model = AutoModelForSeq2SeqLM.from_pretrained("transZ/ViT5-repara") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de10dc338e75549ff46fcfad30d922a6047ec7a6fabe1e47496e160dd265c0b9
- Size of remote file:
- 904 MB
- SHA256:
- 0ab589a736597d0157eb13a5bda47caf97bba4bb91a4b4198427e743ca8233fa
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