Instructions to use dnj0/t5_base_article_sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dnj0/t5_base_article_sum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dnj0/t5_base_article_sum") model = AutoModelForSeq2SeqLM.from_pretrained("dnj0/t5_base_article_sum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70e986de193f08e1b1a824c45d563ecaec123a8f83a45d0e8f6cba9b85902fc6
- Size of remote file:
- 892 MB
- SHA256:
- bdb66abaf61a931ece4e053aa6c1193a7abc758ee6e9bd9c0961bb77eff596b5
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