Instructions to use corranm/test_model_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use corranm/test_model_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="corranm/test_model_7") 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("corranm/test_model_7") model = AutoModelForImageClassification.from_pretrained("corranm/test_model_7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1b652178c4b9937fc546bae9337686e6f9aacf8763b4d132db358adcdedd859
- Size of remote file:
- 343 MB
- SHA256:
- 6448b92ad7f3f5531c908923f72f5ad3529b87c55ecd1178dc964378d5451ac2
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