Instructions to use emilstabil/DanSumT5-largeV_38143 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilstabil/DanSumT5-largeV_38143 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("emilstabil/DanSumT5-largeV_38143") model = AutoModelForSeq2SeqLM.from_pretrained("emilstabil/DanSumT5-largeV_38143", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from emilstabil/DanSumT5-largeV_38143: direct link, hf CLI and curl.
- Browser
- Download file 4.92 GB
-
https://huggingface.co/emilstabil/DanSumT5-largeV_38143/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://emilstabil/DanSumT5-largeV_38143/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/emilstabil/DanSumT5-largeV_38143/resolve/main/pytorch_model.bin
4.92 GB
- Xet hash:
- ebdf357a105504fdd7e41b2be3630c8c21ed66e354212855a221e57eaf624fa0
- Size of remote file:
- 4.92 GB
- SHA256:
- b2d1ba8b0011c0a772593c0fb6088bdfbd8094fa27c5ee0b641983aa78e2a06f
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