Instructions to use vlevi/Main_Fashion-convnext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vlevi/Main_Fashion-convnext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="vlevi/Main_Fashion-convnext") 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("vlevi/Main_Fashion-convnext") model = AutoModelForImageClassification.from_pretrained("vlevi/Main_Fashion-convnext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8f25005c54ac1fd7a4193dcb6b3bbef536113254c040973aaae55eab2c48548
- Size of remote file:
- 111 MB
- SHA256:
- 3c7101c99292b40979692d6b2a1d8a9a9ae310f3577fbbf1dc07d0643f1f10a4
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