Instructions to use sshleifer/student_xsum_12_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_xsum_12_2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_xsum_12_2") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_xsum_12_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6043c61412b9394a298a073c49a3cb704b280946267c84017d8448abb9432829
- Size of remote file:
- 954 MB
- SHA256:
- d9af9b5c3b560f62f20acd4f319f955619b448d3d6b1d37e9be81249ba9036c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.