Upload README.md with huggingface_hub

README.md

@@ -1,21 +1,59 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: filename
-    dtype: string
-  - name: index
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 2997545720
-    num_examples: 10000
-  download_size: 2997686823
-  dataset_size: 2997545720
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: mit
+task_categories:
+- image-classification
+tags:
+- ai-generated
+- sdxl
+- stable-diffusion-xl
+size_categories:
+- 10K<n<100K
 ---
+
+# SDXL Generated Images Dataset (10,000 images)
+
+This dataset contains 10,000 AI-generated images created with Stable Diffusion XL for training an AI image detector.
+
+## Dataset Details
+
+- **Model**: Stable Diffusion XL Base 1.0
+- **Total Images**: 10,000
+- **Resolution**: 1024×1024 pixels
+- **Format**: JPEG (quality 95)
+- **Inference Steps**: 10
+- **Guidance Scale**: 7.0
+- **Random Seeds**: Unique per image for maximum diversity
+- **Generation Date**: 2025-12-30
+
+## Prompt Diversity
+
+Images generated with diverse prompts covering:
+- Portraits and people (various poses, expressions, settings)
+- Landscapes (mountains, oceans, forests, etc.)
+- Objects and still life
+- Animals in natural habitats
+- Food photography
+- Architecture and buildings
+- Various lighting conditions and styles
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load dataset
+dataset = load_dataset("ash12321/sdxl-generated-10k")
+
+# Access images
+for example in dataset["train"]:
+    image = example["image"]
+    filename = example["filename"]
+```
+
+## License
+
+MIT License - Free for research and commercial use.
+
+## Related
+
+- Detector Model: [ash12321/sdxl-detector-resnet50](https://huggingface.co/ash12321/sdxl-detector-resnet50)