Instructions to use youngp5/eyeglasses_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youngp5/eyeglasses_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="youngp5/eyeglasses_detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("youngp5/eyeglasses_detection") model = AutoModelForImageClassification.from_pretrained("youngp5/eyeglasses_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from youngp5/eyeglasses_detection: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/youngp5/eyeglasses_detection/resolve/main/optimizer.pt
- Command line
-
hf download hf://youngp5/eyeglasses_detection/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/youngp5/eyeglasses_detection/resolve/main/optimizer.pt
687 MB
- Xet hash:
- 4aaad0c63ba7ce46e1b8ea6be7840c446e1ed9aedf79e4e3ce640777661e1ed3
- Size of remote file:
- 687 MB
- SHA256:
- d37b1f94d0dd785963f288ea95af59d80bf7fe7b27c861300f7a4effae4f856d
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