Transformers
PyTorch
TensorBoard
encoder-decoder
text2text-generation
simplification
Generated from Trainer
Instructions to use CLARA-MeD/marimari-r2r-mlsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLARA-MeD/marimari-r2r-mlsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CLARA-MeD/marimari-r2r-mlsum") model = AutoModelForSeq2SeqLM.from_pretrained("CLARA-MeD/marimari-r2r-mlsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7019c83b05495d203fa8b041f7c98e64964f2dfec74ba2b9e7c2619f88afcffe
- Size of remote file:
- 615 MB
- SHA256:
- aae3f3ac4a7c1521bccbafb92a88d77f9f84d23cee3fcfc0c376323238438a22
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