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:
- 1ed64685924282917abc63a8c0b7d03b98fb4fff93df0b626accb48e84c1034e
- Size of remote file:
- 1.2 GB
- SHA256:
- 8f5f092cb76f08a6f087fef0b7dd23cb53205594e0660fc5c4a1b69e4ebcbfc6
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