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:
# pip install -U transformers accelerate # 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
Download training_args.bin from CLARA-MeD/marimari-r2r-mlsum: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/CLARA-MeD/marimari-r2r-mlsum/resolve/main/training_args.bin
- Command line
-
hf download hf://CLARA-MeD/marimari-r2r-mlsum/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLARA-MeD/marimari-r2r-mlsum/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- bc9b5451a2f9de46505fa689b9fb780f572e20483ab2eea9fd8c55273f11d98f
- Size of remote file:
- 3.58 kB
- SHA256:
- 1853fb49d4404d3a42f2065cfe435544c6af96cf3a88940221782bb55a232e11
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