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
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -1,3 +1,16 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
# AI Image Detector
|
| 3 |
+
|
| 4 |
+
This model was fine-tuned using MobileNetV2 on CIFAKE dataset.
|
| 5 |
+
|
| 6 |
+
## Features
|
| 7 |
+
- Transfer Learning
|
| 8 |
+
- Fine-Tuning
|
| 9 |
+
- Binary Classification
|
| 10 |
+
- Detects AI vs Real Images
|
| 11 |
+
|
| 12 |
+
## Accuracy
|
| 13 |
+
~92-96%
|
| 14 |
+
|
| 15 |
+
## Framework
|
| 16 |
+
TensorFlow / Keras
|