Instructions to use sshleifer/student_xsum_12_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_xsum_12_4 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_xsum_12_4") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_xsum_12_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6397b438eb1ce925945d38e18563f21cbf0028f40890a5967605e9ef525f891
- Size of remote file:
- 1.09 GB
- SHA256:
- 354dba9f7be3458b7ca7de92ee75cb53bc0d9ccaf63a564e7b0636f5c10f5148
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.