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:
- d9c75198f43a87aacf66cc3b5badee603127c972eb82017f87354e5c6a1457f1
- Size of remote file:
- 4.98 kB
- SHA256:
- abf996139b38bd31f888913470e3ce997f97077ef88c6b30a3bbbbd57f1552f5
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