Instructions to use sshleifer/student_cnn_12_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_cnn_12_2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_cnn_12_2") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_cnn_12_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2116b072372d525aa3f37eb69eb3e497001f322479285f7d1bfd1850d97785ac
- Size of remote file:
- 954 MB
- SHA256:
- 6bb88aa8cf9e5617de38c2aea07004ef1ebc2cf9cf7866b7fa4ff1a01d63229a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.