Video Classification
Transformers
PyTorch
English
afmoe
deepfake-detection
clip
vit
spatiotemporal-adapters
bf16
reproducibility
Instructions to use Begrudging/deepfake-detector-dfd-sota with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Begrudging/deepfake-detector-dfd-sota with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="Begrudging/deepfake-detector-dfd-sota")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Begrudging/deepfake-detector-dfd-sota", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -0
config.json
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{
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"best_val_acc": 84.88372093023256,
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"best_val_loss": 0.6505792791193182
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}
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{
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"model_type": "afmoe",
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"best_val_acc": 84.88372093023256,
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"best_val_loss": 0.6505792791193182
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}
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