Instructions to use BMILab/K-Clinical-T5-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BMILab/K-Clinical-T5-Large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("BMILab/K-Clinical-T5-Large") model = AutoModelForMultimodalLM.from_pretrained("BMILab/K-Clinical-T5-Large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb480c2814af6628e2702dbf952dd8931174d83703653b86305dca8fa83f8891
- Size of remote file:
- 3.13 GB
- SHA256:
- 7ac6a4e570df1037559af0848073cd6030d1b282591458befab24abafd2ae292
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