Instructions to use march18/FacialConfidence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use march18/FacialConfidence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="march18/FacialConfidence") 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("march18/FacialConfidence") model = AutoModelForImageClassification.from_pretrained("march18/FacialConfidence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d3f90aad4dd33df506cb1ba6dbabe7a5d97c8ea931741a684feb9190dd6712f
- Size of remote file:
- 5.18 kB
- SHA256:
- 01747f4854dca9e658aa952b7036768e051561041046121f0cab9af6303566e6
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