Image Classification
Transformers
Safetensors
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use awanicka/TransparentBagClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use awanicka/TransparentBagClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="awanicka/TransparentBagClassifier") 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("awanicka/TransparentBagClassifier") model = AutoModelForImageClassification.from_pretrained("awanicka/TransparentBagClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5715b8eafd54ccbed184639ee88af8d5edbbde5afb8be6fcf650d3d87087a8e5
- Size of remote file:
- 343 MB
- SHA256:
- f42951574fb64d251502b0b15448fcb3fb8bedfe776bba2d8460d2628cdd18df
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