Instructions to use paulh27/xsum_aligned_smallmT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulh27/xsum_aligned_smallmT5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("paulh27/xsum_aligned_smallmT5") model = AutoModelForSeq2SeqLM.from_pretrained("paulh27/xsum_aligned_smallmT5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed12708f2beb42050d4a0fa0b4b3bcaa34acdbeb139d1af636b40f1bdba0b7d0
- Size of remote file:
- 242 MB
- SHA256:
- 667af7eaf182525bbe5fabe7facdfa3ddf6d5dd0d881fe173cb5fb0a67059c13
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