Instructions to use rooftopcoder/tst-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rooftopcoder/tst-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rooftopcoder/tst-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("rooftopcoder/tst-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 228cd5f22a47d5fd32bc84ded84544c0885a903ffac70d06f5d42094f0d67df2
- Size of remote file:
- 558 MB
- SHA256:
- ebd8bda89a388b835d3fe555572d32c19cb0b694e42fade688120667429d0e92
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