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README.md

@@ -14,7 +14,7 @@ tags:
 # YOLOv8-Detection-Quantized: Optimized for Mobile Deployment
 ## Quantized real-time object detection optimized for mobile and edge by Ultralytics
 
-Ultralytics YOLOv8 is a machine learning model that predicts bounding boxes and classes of objects in an image. This model is post-training quantized to int8 using samples from the [COCO dataset](https://cocodataset.org/#home).
+Ultralytics YOLOv8 is a machine learning model that predicts bounding boxes and classes of objects in an image. This model is post-training quantized to int8 using samples from the COCO dataset.
 
 This model is an implementation of YOLOv8-Detection-Quantized found [here](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models/yolo/detect).
 This repository provides scripts to run YOLOv8-Detection-Quantized on Qualcomm® devices.
@@ -34,8 +34,7 @@ More details on model performance across various devices, can be found
 
 | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
 | ---|---|---|---|---|---|---|---|
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 2.122 ms | 0 - 2 MB | INT8 | NPU |  [YOLOv8-Detection-Quantized.tflite](https://huggingface.co/qualcomm/YOLOv8-Detection-Quantized/blob/main/YOLOv8-Detection-Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 2.121 ms | 1 - 11 MB | INT8 | NPU |  [YOLOv8-Detection-Quantized.so](https://huggingface.co/qualcomm/YOLOv8-Detection-Quantized/blob/main/YOLOv8-Detection-Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 2.343 ms | 0 - 2 MB | INT8 | NPU |  [YOLOv8-Detection-Quantized.tflite](https://huggingface.co/qualcomm/YOLOv8-Detection-Quantized/blob/main/YOLOv8-Detection-Quantized.tflite) 
 
 
 ## Installation
@@ -93,23 +92,6 @@ device. This script does the following:
 python -m qai_hub_models.models.yolov8_det_quantized.export
 ```
 
-```
-Profile Job summary of YOLOv8-Detection-Quantized
---------------------------------------------------
-Device: Samsung Galaxy S24 (14)
-Estimated Inference Time: 1.42 ms
-Estimated Peak Memory Range: 0.01-47.27 MB
-Compute Units: NPU (274) | Total (274)
-
-Profile Job summary of YOLOv8-Detection-Quantized
---------------------------------------------------
-Device: Samsung Galaxy S24 (14)
-Estimated Inference Time: 1.42 ms
-Estimated Peak Memory Range: 1.19-102.44 MB
-Compute Units: NPU (272) | Total (272)
-
-
-```
 ## How does this work?
 
 This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/YOLOv8-Detection-Quantized/export.py)