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:
- 48473af5f29d86bdb1342e54235219c0ad5f857f2aa8d19ec0ab3f2a938baacf
- Size of remote file:
- 22.2 MB
- SHA256:
- ab9a363b4c2b647e249e54a9a770676b0f0a8b368c3856ae01a9a3b8bdbdc437
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