Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_faces-expand30-aligned_unaugmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_faces-expand30-aligned_unaugmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_faces-expand30-aligned_unaugmentation") 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("hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_faces-expand30-aligned_unaugmentation") model = AutoModelForImageClassification.from_pretrained("hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_faces-expand30-aligned_unaugmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 183f1e7805cf0ceb4453439cb5299b7e64ae151a7527f7a1293df427a209f329
- Size of remote file:
- 5.24 kB
- SHA256:
- 8549094cc736d6230adc3c94182e6122da1db30e64ced30ae6251a3b15352030
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