Spaces:
Runtime error
Runtime error
| title: PyTorch Lightning | |
| emoji: ๐ | |
| colorFrom: blue | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 3.39.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| Training details: | |
| 1. This model is trained on CIFAR10 with following classes: ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck'] | |
| 2. It is trained on 24 epochs using One Cycle Policy using PyTorch Lightning | |
| Features of spaces app: | |
| 1. User can decide on whether he/she wants to see GradCAM images and how many, and from which layer, allow opacity change as well | |
| 2. User can ask whether he/she wants to view misclassified images, and how many (maximum limit is 50) | |
| 3. User is allowed to upload new images | |
| 4. User can give number of top classes that are to be shown (maximum limit is 10) | |
| 5. 10 example images for each class is provided | |
| Github Link for trained model: https://github.com/MPGarg/ERA1_Session12 | |