Instructions to use sandesh2233/Deepfakes_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sandesh2233/Deepfakes_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sandesh2233/Deepfakes_detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sandesh2233/Deepfakes_detection") model = AutoModelForImageClassification.from_pretrained("sandesh2233/Deepfakes_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b163007d5c48c14eee312e6a032eda6c8a9c7b49ea280ee3ae1fef0df3fc8ce
- Size of remote file:
- 343 MB
- SHA256:
- 5571d40b400b7a70a269db808fd5f26796f113e0233ea93493919bfca19dca44
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