Image Classification
PyTorch
timm
computer-vision
vehicle-classification
fine-grained-classification
Instructions to use twincar-group2/twincar-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use twincar-group2/twincar-classifier with timm:
import timm model = timm.create_model("hf_hub:twincar-group2/twincar-classifier", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Update manifest for EfficientNet-B3 augmentation v2 final checkpoint
Browse files- checkpoint_manifest.json +10 -5
checkpoint_manifest.json
CHANGED
|
@@ -1,15 +1,20 @@
|
|
| 1 |
{
|
| 2 |
"current_candidate": {
|
| 3 |
-
"file": "
|
| 4 |
"architecture": "efficientnet_b3",
|
| 5 |
"image_size": 300,
|
| 6 |
"dataset": "Stanford Cars",
|
| 7 |
"num_classes": 196,
|
| 8 |
-
"
|
| 9 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 10 |
},
|
| 11 |
"previous_baseline": {
|
| 12 |
"file": "best.pt",
|
| 13 |
-
"
|
| 14 |
}
|
| 15 |
-
}
|
|
|
|
| 1 |
{
|
| 2 |
"current_candidate": {
|
| 3 |
+
"file": "efficientnet_b3_stanford300_augv2_best.pt",
|
| 4 |
"architecture": "efficientnet_b3",
|
| 5 |
"image_size": 300,
|
| 6 |
"dataset": "Stanford Cars",
|
| 7 |
"num_classes": 196,
|
| 8 |
+
"train_augmentation": "v2",
|
| 9 |
+
"sha256": "d390d46ea5671f47fc70aa89db1fa579afd11ccc5a0284fa6777c9154edddbf6",
|
| 10 |
+
"status": "current_final_candidate"
|
| 11 |
+
},
|
| 12 |
+
"previous_candidate": {
|
| 13 |
+
"file": "efficientnet_b3_stanford300_best.pt",
|
| 14 |
+
"status": "previous EfficientNet-B3 checkpoint"
|
| 15 |
},
|
| 16 |
"previous_baseline": {
|
| 17 |
"file": "best.pt",
|
| 18 |
+
"status": "older ResNet18 baseline checkpoint"
|
| 19 |
}
|
| 20 |
+
}
|