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:
- e771d56dc0ad7f525743bc94aef42d503977b78aee0686be5bd2f6cbb78d185f
- Size of remote file:
- 5.18 kB
- SHA256:
- 94c151472647030477931230d70b25a7b054d197d7f1a9dc2609416dc98ac19e
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