Instructions to use prithivMLmods/Deepfake-Detection-Exp-02-22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Deepfake-Detection-Exp-02-22 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Deepfake-Detection-Exp-02-22") 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-Detection-Exp-02-22") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Deepfake-Detection-Exp-02-22", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from prithivMLmods/Deepfake-Detection-Exp-02-22: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/prithivMLmods/Deepfake-Detection-Exp-02-22/resolve/main/training_args.bin
- Command line
-
hf download hf://prithivMLmods/Deepfake-Detection-Exp-02-22/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prithivMLmods/Deepfake-Detection-Exp-02-22/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- ba72912ca3e871665b09cfbab60f14454d8a8a423014ddd67ae20f6d21a24648
- Size of remote file:
- 5.24 kB
- SHA256:
- a8b821a7a428ff1821b122e8796fde5b3b9a37a81fff0d4beb6b58653fc2d842
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