Instructions to use dima806/clothes_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/clothes_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/clothes_image_detection") 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("dima806/clothes_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/clothes_image_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97d8627aefe8f8b81699693402bbe5ae1d90edbb059a6c0040ef5ce0856859d9
- Size of remote file:
- 5.3 kB
- SHA256:
- 348a7626fa4c360c7b86e7c9aaa401da6136daa29e45038dc6ab9fa90da3c856
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