Instructions to use stochastic/102722run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stochastic/102722run with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="stochastic/102722run") 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("stochastic/102722run") model = AutoModelForImageClassification.from_pretrained("stochastic/102722run") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a06d1889ad6721affcf2ad33467ce6cf7da817240683b7303295faa5fbf48c08
- Size of remote file:
- 3.38 kB
- SHA256:
- ac7656194c2da24ec56ec20cb8d1dd318e7d3f55641e7eb3dcf66dc87f2071b7
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