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:
- 64254b0b8b99ad454556d9df6e6fb95bcd8926c3828f7e667a6f5c5909621f85
- Size of remote file:
- 558 MB
- SHA256:
- 8e19ed21a806ef72465c69209290bc2f47a88bc9cd2aa978c87e11d5fc94507f
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