Instructions to use SamuelMiller/sum_sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamuelMiller/sum_sum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SamuelMiller/sum_sum") model = AutoModelForSeq2SeqLM.from_pretrained("SamuelMiller/sum_sum") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eec230cc4385d356ce10b22ea459db6ba6e84c0cc4b63994497892c2254607b9
- Size of remote file:
- 242 MB
- SHA256:
- 761e20268e271184ddb41ccd00c385a2d289a4786c9dcb8da371b359f27ee92b
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