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README.md

@@ -33,7 +33,7 @@ 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 | 8.735 ms | 7 - 10 MB | FP16 | NPU |  [FastSam-S.tflite](https://huggingface.co/qualcomm/FastSam-S/blob/main/FastSam-S.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 8.729 ms | 7 - 10 MB | FP16 | NPU |  [FastSam-S.tflite](https://huggingface.co/qualcomm/FastSam-S/blob/main/FastSam-S.tflite) 
 
 
 ## Installation
@@ -91,16 +91,6 @@ device. This script does the following:
 python -m qai_hub_models.models.fastsam_s.export
 ```
 
-```
-Profile Job summary of FastSam-S
---------------------------------------------------
-Device: Samsung Galaxy S24 (14)
-Estimated Inference Time: 6.46 ms
-Estimated Peak Memory Range: 6.04-73.32 MB
-Compute Units: NPU (288) | Total (288)
-
-
-```
 ## How does this work?
 
 This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/FastSam-S/export.py)