Instructions to use Soyoung97/ListT5-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Soyoung97/ListT5-3b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, FiDT5 tokenizer = AutoTokenizer.from_pretrained("Soyoung97/ListT5-3b") model = FiDT5.from_pretrained("Soyoung97/ListT5-3b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Soyoung97/ListT5-3b: direct link, hf CLI and curl.
- Browser
- Download file 5.7 GB
-
https://huggingface.co/Soyoung97/ListT5-3b/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Soyoung97/ListT5-3b/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Soyoung97/ListT5-3b/resolve/main/pytorch_model.bin
5.7 GB
- Xet hash:
- 973966306cfa2653c336e8981a96836846b34613cfb968cc8e59bbf131049859
- Size of remote file:
- 5.7 GB
- SHA256:
- 4599499b099c66fe037782aa0b01db6131ddccc46d5d4d6a63d53100de5c2da5
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