Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
English
vit
huggingpics
Eval Results (legacy)
Instructions to use IrshadG/Clothes_Pattern_Classification_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IrshadG/Clothes_Pattern_Classification_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="IrshadG/Clothes_Pattern_Classification_v2") 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("IrshadG/Clothes_Pattern_Classification_v2") model = AutoModelForImageClassification.from_pretrained("IrshadG/Clothes_Pattern_Classification_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4dbfa6f6c6eec0da2f9655ab7bcd367c6c752322cdcdadefed6ef955243ca4e
- Size of remote file:
- 343 MB
- SHA256:
- 9d128d32a22ed7a3af54dbab85c6b51a1d3dfe8c69639a5b27d9652c78692718
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