Instructions to use JaesonGu/flare-cable-vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JaesonGu/flare-cable-vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JaesonGu/flare-cable-vit") 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("JaesonGu/flare-cable-vit") model = AutoModelForImageClassification.from_pretrained("JaesonGu/flare-cable-vit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bc74f31042459d0caa912dc5517170483779970f10915151be6f7a7ca6bb736
- Size of remote file:
- 5.3 kB
- SHA256:
- dfa039c320789cee342c9781b428086050adc9a2d90086a5d602bc1d8523e962
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