Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use Devarshi/Armature_Defect_Detection_Resin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devarshi/Armature_Defect_Detection_Resin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Devarshi/Armature_Defect_Detection_Resin") 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("Devarshi/Armature_Defect_Detection_Resin") model = AutoModelForImageClassification.from_pretrained("Devarshi/Armature_Defect_Detection_Resin") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
pytorch_model.bin
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runs/Oct09_22-37-13_Devarshis-MacBook-Air.local/events.out.tfevents.1696871237.Devarshis-MacBook-Air.local.18098.0
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