Instructions to use hungphongtrn/vit5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hungphongtrn/vit5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hungphongtrn/vit5-base") model = AutoModelForSeq2SeqLM.from_pretrained("hungphongtrn/vit5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hungphongtrn/vit5-base: direct link, hf CLI and curl.
- Browser
- Download file 904 MB
-
https://huggingface.co/hungphongtrn/vit5-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hungphongtrn/vit5-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hungphongtrn/vit5-base/resolve/main/pytorch_model.bin
904 MB
- Xet hash:
- 78c2f314d2c97496f335413c150960b0f8b9ffe75f50670aad11f2ed0abb2632
- Size of remote file:
- 904 MB
- SHA256:
- d5139a20cef4fd653c39616cfc02fefeb5c09f07191a448e32df2fb4b0d1c4f0
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