Instructions to use cataluna84/pegasus-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cataluna84/pegasus-samsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cataluna84/pegasus-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("cataluna84/pegasus-samsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5418e3fcf9a50adca4bfc9344cf479ef3d512c3daa7ab8e878f2363af2a98666
- Size of remote file:
- 2.28 GB
- SHA256:
- 9000f6ac2b36650c188a15f63b09712007c0647873dce164b36ccd4e3475f4c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.