Instructions to use sshleifer/student_xsum_9_12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_xsum_9_12 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_xsum_9_12") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_xsum_9_12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dafa0d0159ec62ea60610a4fe634e5e0ded6ad392f25a0b9d6f835792cb1101
- Size of remote file:
- 1.47 GB
- SHA256:
- 77238a68a2b466d68130dbba94d425fea26c45637b78f27986d605b9a1dc620a
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