Instructions to use JoonJoon/t5-small-finetuned-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoonJoon/t5-small-finetuned-xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JoonJoon/t5-small-finetuned-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("JoonJoon/t5-small-finetuned-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from JoonJoon/t5-small-finetuned-xsum: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/JoonJoon/t5-small-finetuned-xsum/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JoonJoon/t5-small-finetuned-xsum/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JoonJoon/t5-small-finetuned-xsum/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- 7fb33a5a494a4ecb6e07cffa95eef887849458fb31c66649a03574d508df3c29
- Size of remote file:
- 242 MB
- SHA256:
- 9da1643d76ac574fd66ddf84744d7f5e2f21bebb40069a3d97579a159eee75d2
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