Image Classification
Transformers
TensorBoard
Safetensors
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use hangpatrick92/TransparentBagClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hangpatrick92/TransparentBagClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hangpatrick92/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("hangpatrick92/TransparentBagClassifier") model = AutoModelForImageClassification.from_pretrained("hangpatrick92/TransparentBagClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49714b5f19ea1770d48285834c6bb399601f80a21b3cb8c6b43280601811e1ee
- Size of remote file:
- 343 MB
- SHA256:
- 758138df66c2eac47e697365c5c23c133bbb75ceba8d23704a97739aead82e3b
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