Instructions to use morganchen1007/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morganchen1007/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="morganchen1007/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("morganchen1007/test") model = AutoModelForImageClassification.from_pretrained("morganchen1007/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc4ff79e787aadd7062349a097b0598700bf3efe63a8ebc359b58279bd808798
- Size of remote file:
- 94.4 MB
- SHA256:
- ad831f2c2c7131fe53aa0e3aeb1628989adfec766c875ffe42676e766ec0cf59
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