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README.md

@@ -35,34 +35,33 @@ More details on model performance across various devices, can be found
 
 | Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
 |---|---|---|---|---|---|---|---|---|
-| ResNet-3D | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 21.453 ms | 29 - 921 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 16.315 ms | 0 - 207 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
-| ResNet-3D | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 15.639 ms | 27 - 62 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 12.253 ms | 2 - 50 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
-| ResNet-3D | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 15.569 ms | 28 - 61 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 10.272 ms | 2 - 56 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
-| ResNet-3D | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 20.94 ms | 29 - 921 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | SA7255P ADP | SA7255P | TFLITE | 726.595 ms | 29 - 58 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 21.278 ms | 29 - 922 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | SA8295P ADP | SA8295P | TFLITE | 36.899 ms | 29 - 61 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 21.413 ms | 29 - 921 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | SA8775P ADP | SA8775P | TFLITE | 41.373 ms | 29 - 57 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 35.552 ms | 29 - 59 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
-| ResNet-3D | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 18.051 ms | 64 - 64 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
+| ResNet-3D | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 21.3 ms | 29 - 921 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 16.085 ms | 0 - 218 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
+| ResNet-3D | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 16.105 ms | 29 - 62 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 12.422 ms | 2 - 54 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
+| ResNet-3D | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 14.054 ms | 28 - 62 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 12.295 ms | 2 - 56 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
+| ResNet-3D | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 21.274 ms | 29 - 921 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | SA7255P ADP | SA7255P | TFLITE | 729.974 ms | 29 - 58 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 21.344 ms | 29 - 922 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | SA8295P ADP | SA8295P | TFLITE | 37.968 ms | 29 - 61 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 20.949 ms | 29 - 922 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | SA8775P ADP | SA8775P | TFLITE | 41.233 ms | 29 - 58 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 34.899 ms | 29 - 66 MB | FP16 | NPU | [ResNet-3D.tflite](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.tflite) |
+| ResNet-3D | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 18.055 ms | 65 - 65 MB | FP16 | NPU | [ResNet-3D.onnx](https://huggingface.co/qualcomm/ResNet-3D/blob/main/ResNet-3D.onnx) |
 
 
 
 
 ## Installation
 
-This model can be installed as a Python package via pip.
 
+Install the package via pip:
 ```bash
-pip install "qai-hub-models[resnet_3d]"
+pip install "qai-hub-models[resnet-3d]"
 ```
 
 
-
 ## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
 
 Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
@@ -113,7 +112,7 @@ Profiling Results
 ResNet-3D
 Device                          : Samsung Galaxy S23 (13) 
 Runtime                         : TFLITE                  
-Estimated inference time (ms)   : 21.5                    
+Estimated inference time (ms)   : 21.3                    
 Estimated peak memory usage (MB): [29, 921]               
 Total # Ops                     : 55                      
 Compute Unit(s)                 : NPU (50 ops) CPU (5 ops)
@@ -141,7 +140,7 @@ from qai_hub_models.models.resnet_3d import Model
 torch_model = Model.from_pretrained()
 
 # Device
-device = hub.Device("Samsung Galaxy S23")
+device = hub.Device("Samsung Galaxy S24")
 
 # Trace model
 input_shape = torch_model.get_input_spec()
@@ -219,7 +218,8 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 
 
 ## License
-* The license for the original implementation of ResNet-3D can be found [here](https://github.com/pytorch/vision/blob/main/LICENSE).
+* The license for the original implementation of ResNet-3D can be found
+  [here](https://github.com/pytorch/vision/blob/main/LICENSE).
 * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)