Instructions to use Surbhit/t5-small_summarizer_billsum-dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Surbhit/t5-small_summarizer_billsum-dataset with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Surbhit/t5-small_summarizer_billsum-dataset") model = AutoModelForSeq2SeqLM.from_pretrained("Surbhit/t5-small_summarizer_billsum-dataset") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45c745cb68b272170dee0cc6611cb4b6cb06a00ae37261891e46071052eec538
- Size of remote file:
- 4.73 kB
- SHA256:
- 98cb16fa433f74dd83d212b21d1f8043bf32fb8d753024e114995465d1bc73c5
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