Instructions to use emilstabil/DanSumT5-smallV_91332 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilstabil/DanSumT5-smallV_91332 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("emilstabil/DanSumT5-smallV_91332") model = AutoModelForSeq2SeqLM.from_pretrained("emilstabil/DanSumT5-smallV_91332", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 761e18efc6102eb8db93f21fd1cfb66bb531537fb6d07edc04b81117de5a37d6
- Size of remote file:
- 4.14 kB
- SHA256:
- 596da540de8229e6deb2e9d10d13bfcf0e41214975f2387c10afab57a686c4d1
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