Instructions to use sshleifer/student_pegasus_xsum_16_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_pegasus_xsum_16_4 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_pegasus_xsum_16_4") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_pegasus_xsum_16_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cebe20f407ed8c7bb5e9db751a15aa9e970676db9286b7963652d3bfe1bad58
- Size of remote file:
- 1.47 GB
- SHA256:
- 183cad4c904262e634e06f06125e557c5c6f5a077e29057c54440c77a73fccad
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