Instructions to use corranm/model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use corranm/model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="corranm/model2") 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/model2") model = AutoModelForImageClassification.from_pretrained("corranm/model2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc430d87e2eacd16b3f9eccd287d69b25f09bc5f8136dcd0c6201813de593629
- Size of remote file:
- 343 MB
- SHA256:
- 2aff61735bef1986c70749341652da8a6514efec879b3dcfc5a31759a3d8c4bc
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