Instructions to use 3145tttt/diffusion-classification_base_resnet_50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3145tttt/diffusion-classification_base_resnet_50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="3145tttt/diffusion-classification_base_resnet_50") 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("3145tttt/diffusion-classification_base_resnet_50") model = AutoModelForImageClassification.from_pretrained("3145tttt/diffusion-classification_base_resnet_50") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51d0022cd6ceb364f800c18f46caf499c703e40cc4fc441875b4044fb7ae169b
- Size of remote file:
- 94.5 MB
- SHA256:
- c2f569fc26a7169839bfbd548c13c55a990bea812e674749be6b95aae79dbb4a
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