Instructions to use Abdulhaque/cancer-type-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Abdulhaque/cancer-type-classification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Abdulhaque/cancer-type-classification") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Cancer Type Classification Model
Model Info
- Architecture: ConvNeXt-Base
- Task: 5-class Cancer Type Classification
- Input: 224x224x3 histopathology images
Classes
- 0: Lung Adenocarcinoma
- 1: Lung Squamous Cell Carcinoma
- 2: Colon Adenocarcinoma
- 3: Lung Normal
- 4: Colon Normal
Performance
| Metric | Value |
|---|---|
| Val Accuracy | 94.19% |
| Test Accuracy | 94.0% |
| Val AUC | 0.9942 |
Usage
import tensorflow as tf
model = tf.keras.models.load_model('best_model_ft.keras')
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