Instructions to use changsu/testmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use changsu/testmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="changsu/testmodel") 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("changsu/testmodel") model = AutoModelForImageClassification.from_pretrained("changsu/testmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9feca7d3ac9f56650ca19a35122fc0b39c857efdba0cf3509d25adcfd8fa8fd2
- Size of remote file:
- 343 MB
- SHA256:
- 595fb4ea66037f545417e0c87ad44b3568431a2e3eae9f0ff3f089cedb1fd696
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