Instructions to use ErnestBeckham/MulticancerViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ErnestBeckham/MulticancerViT with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://ErnestBeckham/MulticancerViT") - Notebooks
- Google Colab
- Kaggle
Model description
This is Vision Transformer model trained for cancer classification. To make single model to predict any cancer, I trained this ViT model. following are the cancer types that model can predict:
- Brain cancer
- Breast Cancer (histopathology)
- Lung & Colon Cancer (histopathology)
- Cervical Caner
- Kidney Cancer
- Lymphoma
- Oral
Intended uses & limitations
More information needed
Training and evaluation data
Confusion matrix and classification report attached below:
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
| Hyperparameters | Value |
|---|---|
| name | Adam |
| learning_rate | 0.0001 |
| decay | 0.0 |
| beta_1 | 0.9 |
| beta_2 | 0.999 |
| epsilon | 1e-07 |
| amsgrad | False |
| training_precision | float32 |
Model Plot
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