Instructions to use agestau/fashion_classification_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agestau/fashion_classification_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="agestau/fashion_classification_2") 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("agestau/fashion_classification_2") model = AutoModelForImageClassification.from_pretrained("agestau/fashion_classification_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86bc867a1aeb5633a2ca9848fead7d6977bba65f22e5962daac38f2a5195e071
- Size of remote file:
- 3.64 kB
- SHA256:
- 4c7a1504c8e4165ed33ff9c0be09b617f6136cf598d03dbd864fa67c1ebabd03
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