Instructions to use lvwerra/pegasus-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lvwerra/pegasus-samsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lvwerra/pegasus-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("lvwerra/pegasus-samsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d92c1bd9845b559b3a922f1b39fec77e51d427e5fad5d4c4388a89dab154cc7
- Size of remote file:
- 2.28 GB
- SHA256:
- eab20415c0af9a9e3670f7da4320a3825697f9953ca448b8638a43a651a7338c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.