Image Classification
Transformers
PyTorch
English
vision
damage-detection
classification
vit
household-items
Instructions to use narinzar/damage-classifier-multi-task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use narinzar/damage-classifier-multi-task with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="narinzar/damage-classifier-multi-task") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("narinzar/damage-classifier-multi-task", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20b76402a0e0698bd845ba4e41730af0637f0de64ca236b102a167469d112040
- Size of remote file:
- 343 MB
- SHA256:
- c329f6d00dbf50e3d446e92ee1d26a613f861274f1b892f2383f509d03676eab
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