Image Classification
Transformers
Safetensors
English
clip
zero-shot-image-classification
multi-task-classification
fairface
vision
autoeval-has-no-ethical-license
Eval Results (legacy)
Instructions to use syntheticbot/clip-face-attribute-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syntheticbot/clip-face-attribute-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="syntheticbot/clip-face-attribute-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("syntheticbot/clip-face-attribute-classifier") model = AutoModelForZeroShotImageClassification.from_pretrained("syntheticbot/clip-face-attribute-classifier") - Notebooks
- Google Colab
- Kaggle
Ctrl+K