Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use IrshadG/Clothes_Classification_hnm_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IrshadG/Clothes_Classification_hnm_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="IrshadG/Clothes_Classification_hnm_1") 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_Classification_hnm_1") model = AutoModelForImageClassification.from_pretrained("IrshadG/Clothes_Classification_hnm_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84f425c0e4ad5c1350ed4bb6a13ed3b4c18ea3f09480fb3745a6ca9c545bef0a
- Size of remote file:
- 343 MB
- SHA256:
- df5437fbb744e81924d7573bb3a1300cdc2789d4a671f4dacb9d53885a095438
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