Instructions to use JungHun/pegasus-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JungHun/pegasus-samsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JungHun/pegasus-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("JungHun/pegasus-samsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 142f071b5c8f14e5e249042b1437bf961356070666f5bb4b86acf54044befe28
- Size of remote file:
- 2.28 GB
- SHA256:
- bc117be73695150e3abb880d39b1ba2b83b80cb184a88ba7a3886a3de9684067
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.