Instructions to use sshleifer/student_xsum_6_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_xsum_6_6 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_xsum_6_6") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_xsum_6_6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa67dceb3168a849e53d88ec7f84879e4a72081c55e28ce0a7f63dfdf1e9c185
- Size of remote file:
- 920 MB
- SHA256:
- 6d1c7f866c08587573f820cf26b8a515e4e684f109804b35f59b3abd9b706c45
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