Instructions to use flyingbugs/style_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flyingbugs/style_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="flyingbugs/style_classification") 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") model = AutoModelForImageClassification.from_pretrained("flyingbugs/style_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bae106d213a306a0dc6e94b214921609456e9d38552f5acaca513160e16b023
- Size of remote file:
- 343 MB
- SHA256:
- b52de458b66ada7eb02c2d146895b37ed7eff3e76c1f7f37d46a6c7dae5f9997
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.