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# from super_gradients.training import models
# yolo_nas_l = models.get("yolo_nas_s", pretrained_weights="coco")
ImportError Traceback (most recent call last)
…
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### 💡 Your Question
where can I find or how to do inferencing using onnx?
There are example how to conver to onnx from pth file.
```
# Convert model to onnx
torch.onnx.export(model, dummy_inp…
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### 💡 Your Question
1.I now load the model via
model = models.get(
args['model'],
num_classes=len(yaml_params['names']),
checkpoint_path=args["weight"]
)
2.predicte…
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### 💡 Your Question
I don't know why but when I want to start training from the last checkpoint based on what is in here: https://github.com/Deci-AI/super-gradients/blob/b4eec926261e9e8f3032d8fb51977…
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Does Yolo-nas support training with multi-scale ?
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Its better to take class name after loading the model like YOLOv7 and YOLOv8.
Rather than while predicting
In YOLOv7 and YOLOv8 we can take class names:
```
model = YOLO(model_path)
class_names…
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Currently, a Weights & Biases run is initialized inside the constructor of [`WandBSGLogger`](https://github.com/Deci-AI/super-gradients/blob/master/src/super_gradients/common/sg_loggers/wandb_sg_logge…
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### Search before asking
- [X] I have searched the YOLOv8 [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and fou…
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Instantiating a YOLONAS model for fine-tuning:
`model = models.get('yolo_nas_l', num_classes=len(dataset_params['classes']), pretrained_weights="coco")`
Line above works, but following line (jus…
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### 💡 Your Question
I have this code:
```
image = cv2.imread(image_path, cv2.IMREAD_UNCHANGED)
if image.shape[0] != 640 or image.shape[1] != 640:
image = cv2.resize(image, (640, 640))
# …