Instructions to use dima806/face_obstruction_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/face_obstruction_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/face_obstruction_image_detection") 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("dima806/face_obstruction_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/face_obstruction_image_detection") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:5be92c27b0e29e75ee75280e66ebf6075b1045951f2a739b7b78ecf782147b56
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size 343236280
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