Instructions to use emilstabil/DanSumT5-largeV_38143V_15157 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilstabil/DanSumT5-largeV_38143V_15157 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("emilstabil/DanSumT5-largeV_38143V_15157") model = AutoModelForSeq2SeqLM.from_pretrained("emilstabil/DanSumT5-largeV_38143V_15157", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from emilstabil/DanSumT5-largeV_38143V_15157: direct link, hf CLI and curl.
- Browser
- Download file 4.92 GB
-
https://huggingface.co/emilstabil/DanSumT5-largeV_38143V_15157/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://emilstabil/DanSumT5-largeV_38143V_15157/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/emilstabil/DanSumT5-largeV_38143V_15157/resolve/main/pytorch_model.bin
4.92 GB
- Xet hash:
- ebd730c2381640a859f2ee7def678ae1b49a3dc12ad6fff8fc324f414caa8e56
- Size of remote file:
- 4.92 GB
- SHA256:
- bf4b2fb1d36b2845009fd06e78bf192c48d429390f87b2a00d7c3847caab0c05
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