Instructions to use Linhz/AlphaEdu_ViT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Linhz/AlphaEdu_ViT5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Linhz/AlphaEdu_ViT5") model = AutoModelForSeq2SeqLM.from_pretrained("Linhz/AlphaEdu_ViT5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15e1774ecc6ef34def34bdfd76c56960d8acf67b7616a749ee87670d27595fdc
- Size of remote file:
- 14.2 kB
- SHA256:
- 8c051804575f9fa0c9caf29c037731ec19548478b43e17a6493bb7c674ff9718
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