Instructions to use nhanv/vit5-absum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhanv/vit5-absum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nhanv/vit5-absum") model = AutoModelForSeq2SeqLM.from_pretrained("nhanv/vit5-absum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from nhanv/vit5-absum: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/nhanv/vit5-absum/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://nhanv/vit5-absum/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/nhanv/vit5-absum/resolve/main/flax_model.msgpack
990 MB
- Xet hash:
- 06029ad873793413b97ea370a00ce1593c54b1905463dffbf0c50601cf48bc54
- Size of remote file:
- 990 MB
- SHA256:
- 7ad431b1aff9f878d42d13f73f177a047b95c13ba0bf6d5583bfc0b1f3bc3f73
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