Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use hchcsuim/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hchcsuim/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hchcsuim/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std") 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/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std") model = AutoModelForImageClassification.from_pretrained("hchcsuim/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f3349e3e4c1024334824a492e5659614ed9c7c3566164fc8f67eed968cf8c64
- Size of remote file:
- 5.05 kB
- SHA256:
- c4b5d54689d3c8d59d5096972d27912d1170f66844ff0730f94724aa7a132b8d
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