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:
- d930ff21fabe25278ee65298d00fe1275c25629a6851bbdb8a9fec3ff7ec2bed
- Size of remote file:
- 4.98 kB
- SHA256:
- 368cc45235d9f4ed8410f65de1282cd756bc99e7cdd1e6c7d7153666dcc94a8d
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