Image Classification
Transformers
TensorBoard
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use embunna/resnet-18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use embunna/resnet-18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="embunna/resnet-18") 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") model = AutoModelForImageClassification.from_pretrained("embunna/resnet-18") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a0b6a2e3d30e60140f7db6bb1ef6d43c7859ba0b52c0a47683c13d80f29596d
- Size of remote file:
- 5.11 kB
- SHA256:
- a4510e39fc69d06cfadbe8aeabda68062b30b7ff3b10f556d9764d556cb7aeb3
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