Instructions to use kolkela/simple-cnn-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kolkela/simple-cnn-classifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kolkela/simple-cnn-classifier") - Notebooks
- Google Colab
- Kaggle
metadata
language: en
tags:
- keras
- computer-vision
- image-classification
- cnn
license: mit
Simple CNN Classifier
Model Architecture
- Data Augmentation: Random Flip, Rotation, Zoom, Contrast
- Conv Blocks: 32 -> 64 -> 128 filters + MaxPool
- Regularization: Dropout
- Head: GlobalAveragePooling2D -> Dense Layer
How to Load & Use
import keras
model = keras.saving.load_model("hf://kolkela/simple-cnn-classifier")