Instructions to use kaczmarj/pancancer-tissue-classifier.tcga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaczmarj/pancancer-tissue-classifier.tcga with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kaczmarj/pancancer-tissue-classifier.tcga", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "spec_version": "1.0", | |
| "type": "clam", | |
| "patch_size_um": 128, | |
| "feature_extractor": "ctranspath", | |
| "num_classes": 32, | |
| "class_names": [ | |
| "ACC", | |
| "BLCA", | |
| "BRCA", | |
| "CESC", | |
| "CHOL", | |
| "COAD", | |
| "DLBC", | |
| "ESCA", | |
| "GBM", | |
| "HNSC", | |
| "KICH", | |
| "KIRC", | |
| "KIRP", | |
| "LGG", | |
| "LIHC", | |
| "LUAD", | |
| "LUSC", | |
| "MESO", | |
| "OV", | |
| "PAAD", | |
| "PCPG", | |
| "PRAD", | |
| "READ", | |
| "SARC", | |
| "SKCM", | |
| "STAD", | |
| "TGCT", | |
| "THCA", | |
| "THYM", | |
| "UCEC", | |
| "UCS", | |
| "UVM" | |
| ] | |
| } | |