Instructions to use bayat10/media-authenticity-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bayat10/media-authenticity-models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bayat10/media-authenticity-models") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import GenD model = GenD.from_pretrained("bayat10/media-authenticity-models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
Upload hf-models/DeCoF.tar with huggingface_hub c5cda4e verified
Delete models 4a6aae7 verified
Add GenD_DINOv3_L model (server-side copy) 1ea87c1 verified
Add GenD_DINOv3_L config.json (server-side transfer) 8b3ee02 verified
Add GenD_DINOv3_L README.md (server-side transfer) a49f9cb verified
Add pretrained model weights 3a1e95e
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