Instructions to use branyo/small384-sticker1-0.25-boost with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use branyo/small384-sticker1-0.25-boost with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="branyo/small384-sticker1-0.25-boost") 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("branyo/small384-sticker1-0.25-boost") model = AutoModelForImageClassification.from_pretrained("branyo/small384-sticker1-0.25-boost", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 532a0bed4e442e1a4b2f9dd178154596f6bd573bfb8c6f1d96e192db97895bb7
- Size of remote file:
- 86.7 MB
- SHA256:
- 54de4c203b86aa9bd3be8fc8157f6175016307d79bffdce93d26b2381c1c174b
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