Image Classification
Transformers
Safetensors
Spanish
vit
vision-transformer
binary-classification
deepfake-detection
Instructions to use djramirezp/vit-face-classification-quiz2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djramirezp/vit-face-classification-quiz2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="djramirezp/vit-face-classification-quiz2") 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("djramirezp/vit-face-classification-quiz2") model = AutoModelForImageClassification.from_pretrained("djramirezp/vit-face-classification-quiz2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d60b6c2bf58e659d68323d1e13388545dde95d58c98f3f411cd5e82413be9eee
- Size of remote file:
- 5.43 kB
- SHA256:
- 996910b20e8895000999ca655730e24555f2998d3c6e626c04f395fdf89b53f1
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