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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Linhz/AlphaEdu_ViT5") model = AutoModelForSeq2SeqLM.from_pretrained("Linhz/AlphaEdu_ViT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Linhz/AlphaEdu_ViT5: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/Linhz/AlphaEdu_ViT5/resolve/main/training_args.bin
- Command line
-
hf download hf://Linhz/AlphaEdu_ViT5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Linhz/AlphaEdu_ViT5/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- fcb7a6a7a468d140d781ab13f12c4470f6b47a8ee48792b45d7514b109430647
- Size of remote file:
- 5.05 kB
- SHA256:
- b45120183b5d7a3fd1b1120ecde68bed3abc08ba4dd9852412ce2e2cb3b01a89
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