Instructions to use prithivMLmods/Deepfake-QualityAssess-85M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Deepfake-QualityAssess-85M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Deepfake-QualityAssess-85M") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("prithivMLmods/Deepfake-QualityAssess-85M") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Deepfake-QualityAssess-85M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download Builder Script/builder.script.trainner.ipynb from prithivMLmods/Deepfake-QualityAssess-85M: direct link, hf CLI and curl.
- Browser
- Download file 15.1 kB
-
https://huggingface.co/prithivMLmods/Deepfake-QualityAssess-85M/resolve/main/Builder%20Script/builder.script.trainner.ipynb
- Command line
-
hf download 'hf://prithivMLmods/Deepfake-QualityAssess-85M/Builder Script/builder.script.trainner.ipynb'
-
curl -L -o builder.script.trainner.ipynb https://huggingface.co/prithivMLmods/Deepfake-QualityAssess-85M/resolve/main/Builder%20Script/builder.script.trainner.ipynb
15.1 kB