Image Classification
Transformers
Safetensors
vit
deep-fake
ViT
detection
Image
transformers-4.49.0.dev0
precision-92.12
v2
Instructions to use prithivMLmods/Deep-Fake-Detector-v2-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Deep-Fake-Detector-v2-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Deep-Fake-Detector-v2-Model") 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/Deep-Fake-Detector-v2-Model") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Deep-Fake-Detector-v2-Model", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download checkpoint-5252/optimizer.pt from prithivMLmods/Deep-Fake-Detector-v2-Model: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/Deep-Fake-Detector-v2-Model/resolve/main/checkpoint-5252/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/Deep-Fake-Detector-v2-Model/checkpoint-5252/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/Deep-Fake-Detector-v2-Model/resolve/main/checkpoint-5252/optimizer.pt
687 MB
- Xet hash:
- bcbe41d79cf7cb5b260d2a7a93e294444d0697121f058bc7652204e622a2a944
- Size of remote file:
- 687 MB
- SHA256:
- 153aa259991e716cdd80eb64b8e893699d2b7918922e047777037df4359701fe
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