Instructions to use universalml/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalml/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="universalml/test2") 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("universalml/test2") model = AutoModelForImageClassification.from_pretrained("universalml/test2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d473f8c8031573247e8cc42bcf2235c6651ae07d62bd44629dfe1ca19903fd34
- Size of remote file:
- 343 MB
- SHA256:
- c799b8f14449fdacf6ab8cc90401536d7127c4e0f2835f62391ba27d6d07af5e
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