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:
- 1024b1630f51d37481a292e63d5e6c3313fc67e26ae588415c87a72ca4528174
- Size of remote file:
- 171 MB
- SHA256:
- a776f590daf1fee5f73ed7be8d79a6ad22391206dbe750761262b3eb6655698f
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