Instructions to use macroadster/starlight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macroadster/starlight with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="macroadster/starlight") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("macroadster/starlight", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 430 Bytes
2efbe7f | 1 2 3 4 5 6 7 8 9 10 11 | {
"model_type": "onnx",
"task": "steganography-detection",
"architecture": "multi-stream-cnn",
"input_names": ["meta", "alpha", "lsb", "palette", "format_features", "content_features", "bit_order"],
"output_names": ["stego_logits", "method_logits", "method_id", "method_probs", "embedding"],
"method_labels": ["alpha", "palette", "lsb.rgb", "exif", "raw"],
"image_size": 256,
"num_classes": 2,
"num_methods": 5
} |