Instructions to use RUCAIBox/live-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RUCAIBox/live-t5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RUCAIBox/live-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("RUCAIBox/live-t5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from RUCAIBox/live-t5-base: direct link, hf CLI and curl.
- Browser
- Download file 1 GB
-
https://huggingface.co/RUCAIBox/live-t5-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://RUCAIBox/live-t5-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RUCAIBox/live-t5-base/resolve/main/pytorch_model.bin
1 GB
- Xet hash:
- 3f88750da7fcc36f70c3e64026c30ce83478c412b9125fb6c6dd23bad3bf451e
- Size of remote file:
- 1 GB
- SHA256:
- 95603dbc09e2fe89f9cd243c18315df96a80e87abe255c0a5eb1d06d04e7a2b7
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