Instructions to use flyingbugs/style_classification_multiple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flyingbugs/style_classification_multiple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="flyingbugs/style_classification_multiple") 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("flyingbugs/style_classification_multiple") model = AutoModelForImageClassification.from_pretrained("flyingbugs/style_classification_multiple") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a266f1ea7e40abbaa4238927e3c2d0d90d7c6312933e1fdc7e8cb0043d5a28d2
- Size of remote file:
- 343 MB
- SHA256:
- f3d4373a501f536e1ee236bc9ac5e0ea6f6b8947f2620f20d9e75f60b657f067
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.