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
Main_Fashion-convnext / runs /May01_18-45-21_13983870a714 /events.out.tfevents.1714589132.13983870a714.1243.2
- Xet hash:
- f68085aa1c74da1dcdba634a28ca217d7ddc47b2efd610bc221330f2f69437db
- Size of remote file:
- 12.4 kB
- SHA256:
- 492b04bbb1e591d0c87e5af5297ceb412e642255e551ddb833693b897872b52b
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