Instructions to use flyswot/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flyswot/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="flyswot/test") 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("flyswot/test") model = AutoModelForImageClassification.from_pretrained("flyswot/test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b59bd51619051552e0b937bc9c2df3b5f489ab2ffae49108d4f24fb4f12a7abd
- Size of remote file:
- 3.32 kB
- SHA256:
- d442dae9fdc96e8d243bf24fa8f2ac35a3bb989e5dba90d040da9594cc2e1d28
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