Instructions to use PursuitOfDataScience/t5-base-summary-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PursuitOfDataScience/t5-base-summary-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PursuitOfDataScience/t5-base-summary-model") model = AutoModelForSeq2SeqLM.from_pretrained("PursuitOfDataScience/t5-base-summary-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90303838ead34a305f6e95612c1c42a011efa8a8597d1e7a3d8e0e3ee8b1d90f
- Size of remote file:
- 5.11 kB
- SHA256:
- ce515a4e6f6dc4ea463ed043f675774523f1fb852cb08233101de5c12c2d2d63
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