Instructions to use PSW/summ-grounded-method-samsum-reverse-trained-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PSW/summ-grounded-method-samsum-reverse-trained-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PSW/summ-grounded-method-samsum-reverse-trained-model") model = AutoModelForSeq2SeqLM.from_pretrained("PSW/summ-grounded-method-samsum-reverse-trained-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c97f5602f8520b1d669298370a3f0d6f171a2d584ce4de516cc9ef01c9256ae
- Size of remote file:
- 558 MB
- SHA256:
- 6bf7013711966cf1964c94f9acc5f35a06f3aff35e5c22742dab7a243f906559
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