Image Classification
Transformers
PyTorch
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use varcoder/resnet-101-finetuned-CivilEng11k-newDS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/resnet-101-finetuned-CivilEng11k-newDS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="varcoder/resnet-101-finetuned-CivilEng11k-newDS") 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("varcoder/resnet-101-finetuned-CivilEng11k-newDS") model = AutoModelForImageClassification.from_pretrained("varcoder/resnet-101-finetuned-CivilEng11k-newDS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 604dd3e97db39d010d31b3d9aa5c700ca5c810231d3b0ed9bcb8e147f365113a
- Size of remote file:
- 171 MB
- SHA256:
- b4c2400e951f4abfc5c69ee68b83107ae68bff636019d08caa8f081113f8d3d0
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