Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_faces-expand50-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-expand50-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-expand50-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-expand50-aligned_unaugmentation") model = AutoModelForImageClassification.from_pretrained("hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_faces-expand50-aligned_unaugmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8fa11708fa913bf0ead3f7578582d76a97aaf70fb8d4aab16a859d610880add
- Size of remote file:
- 5.24 kB
- SHA256:
- 4052e21eae634805322eeb3c276c163141b92228961ee6fe02b99e1738b921a6
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