Instructions to use Linhz/vit5_viquad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Linhz/vit5_viquad with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Linhz/vit5_viquad") model = AutoModelForSeq2SeqLM.from_pretrained("Linhz/vit5_viquad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f72fb7bdb5408a2f7903387bcec9b5f16cb04a6e40597b53811a811ef7166d48
- Size of remote file:
- 904 MB
- SHA256:
- 11aeac79d1c6ef582f06a9310048330e12149e17fe82164ead0831c27321968e
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