Instructions to use IndianaUniversityDatasetsModels/MIMIC-Medical-Report-Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IndianaUniversityDatasetsModels/MIMIC-Medical-Report-Generator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("IndianaUniversityDatasetsModels/MIMIC-Medical-Report-Generator") model = AutoModelForSeq2SeqLM.from_pretrained("IndianaUniversityDatasetsModels/MIMIC-Medical-Report-Generator") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8a229dc2611c9a713f87c9bbe8140ee25366778a0a97755cf4031d0a90826c9
- Size of remote file:
- 980 MB
- SHA256:
- 83ff0891ce6e9803a275ff3c1398eab384eb43aee5a20d4468f2a92432885b43
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.