Instructions to use syeda-Rija20/image-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use syeda-Rija20/image-detector with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://syeda-Rija20/image-detector") - Notebooks
- Google Colab
- Kaggle
| # AI Image Detector | |
| This model was fine-tuned using MobileNetV2 on CIFAKE dataset. | |
| ## Features | |
| - Transfer Learning | |
| - Fine-Tuning | |
| - Binary Classification | |
| - Detects AI vs Real Images | |
| ## Accuracy | |
| ~92-96% | |
| ## Framework | |
| TensorFlow / Keras | |