Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use metadome/face_shape_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use metadome/face_shape_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="metadome/face_shape_classification") 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("metadome/face_shape_classification") model = AutoModelForImageClassification.from_pretrained("metadome/face_shape_classification") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- b826618ae97028cf38cabec60d2a2e7f6b8f52c967819d8f53ca34003f96c1fd
- Size of remote file:
- 22.7 kB
- SHA256:
- 6ff79631889e93eeae1e60a367977a7efe5fe1c4294a1402008b568c257e9a9f
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