Instructions to use paulh27/xsum_aligned_smallT5_iter2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulh27/xsum_aligned_smallT5_iter2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("paulh27/xsum_aligned_smallT5_iter2") model = AutoModelForSeq2SeqLM.from_pretrained("paulh27/xsum_aligned_smallT5_iter2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30989e89e2b7c2b1b0b131dffd26d8503ea2a11eb29ce3c7be8fe38f87d679f7
- Size of remote file:
- 242 MB
- SHA256:
- 9760c6ca78eae2de4692d8e47c8ffbf985475ca3e7401a69544f3be0f29cf0bf
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