Image Classification
Transformers
TensorBoard
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use embunna/resnet-18-please-work with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use embunna/resnet-18-please-work with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="embunna/resnet-18-please-work") 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("embunna/resnet-18-please-work") model = AutoModelForImageClassification.from_pretrained("embunna/resnet-18-please-work") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0891c16dc7ef3cf06b7aa53a1ccd034e7e2e545da7cb8fe4559d579d13a8b8bc
- Size of remote file:
- 5.11 kB
- SHA256:
- bb466a2f2db48e6ecadee1140e30b908965570e8c819fe5c6ce23659864effa3
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