Instructions to use godiec/diam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use godiec/diam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="godiec/diam") 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("godiec/diam") model = AutoModelForImageClassification.from_pretrained("godiec/diam") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4bdb30fb9f1e345f241d59087c2f0ceff8fd7baf2322680de81aec238a8cc24
- Size of remote file:
- 343 MB
- SHA256:
- a976aad8c7b7d86e89a20f27cbfa5336f5bc9c613f03b71f0d588455c065bcf3
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