Instructions to use kenghweetan/clothing_category_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kenghweetan/clothing_category_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kenghweetan/clothing_category_model") 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("kenghweetan/clothing_category_model") model = AutoModelForImageClassification.from_pretrained("kenghweetan/clothing_category_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17adc34248a99a8db9b718c8fb4c0b288a77456c868d3d6ccef0ad550a608498
- Size of remote file:
- 343 MB
- SHA256:
- c4e80b40a914125f059d472057216e12094ca3d5a1aae0df0d7a4d61da8d8035
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