Upload README.md with huggingface_hub

README.md

@@ -33,8 +33,8 @@ 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 | 1.142 ms | 0 - 1 MB | INT8 | NPU |  [XLSR-Quantized.tflite](https://huggingface.co/qualcomm/XLSR-Quantized/blob/main/XLSR-Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.798 ms | 0 - 71 MB | INT8 | NPU |  [XLSR-Quantized.so](https://huggingface.co/qualcomm/XLSR-Quantized/blob/main/XLSR-Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.13 ms | 0 - 1 MB | INT8 | NPU |  [XLSR-Quantized.tflite](https://huggingface.co/qualcomm/XLSR-Quantized/blob/main/XLSR-Quantized.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.794 ms | 0 - 10 MB | INT8 | NPU |  [XLSR-Quantized.so](https://huggingface.co/qualcomm/XLSR-Quantized/blob/main/XLSR-Quantized.so) 
 
 
 ## Installation
@@ -42,10 +42,11 @@ More details on model performance across various devices, can be found
 This model can be installed as a Python package via pip.
 
 ```bash
-pip install qai-hub-models
+pip install "qai-hub-models[xlsr_quantized]"
 ```
 
 
+
 ## 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
@@ -95,7 +96,7 @@ python -m qai_hub_models.models.xlsr_quantized.export
 Profile Job summary of XLSR-Quantized
 --------------------------------------------------
 Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 0.93 ms
+Estimated Inference Time: 0.95 ms
 Estimated Peak Memory Range: 0.05-0.05 MB
 Compute Units: NPU (17) | Total (17)