Instructions to use james-burton/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use james-burton/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="james-burton/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("james-burton/test") model = AutoModelForImageClassification.from_pretrained("james-burton/test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fc6890b86c5fdb1cf715b24d246ea0db03d6af9cfb92bc2643ffff1e2359fa8
- Size of remote file:
- 4.86 kB
- SHA256:
- bf85df85ac87760d3117c6911e8713dacf4c0df3b705a14f35c5188bbf5c80d0
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