[DOCS] [IRD Vision] model paths in docs updated to latest (open-edge-platform#2159)

Author: sajeevrajput

manufacturing-ai-suite/industrial-edge-insights-vision/docs/user-guide/pallet-defect-detection/get-started/deploy-multiple-instances-with-helm.md

@@ -807,7 +807,7 @@ Applications can take advantage of S3 publish feature from DL Streamer Pipeline
    >NOTE- For sake of simplicity, we assume that the new model has already been downloaded by Model Download microservice. The following curl command is only a simulation that just downloads the model. In production, however, they will be downloaded by the Model Download service.
 
    ```sh
-   export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/1d40dfe1791d44e8cf6e8472c28c034e40fa508d/models/INT8/pallet_defect_detection.zip'
+   export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/06bb0d621cb14a1791672552a538beddddcc4066/models/INT8/pallet_defect_detection.zip'
 
    curl -L "$MODEL_URL" -o "$(basename $MODEL_URL)"
 

manufacturing-ai-suite/industrial-edge-insights-vision/docs/user-guide/pallet-defect-detection/get-started/deploy-with-helm.md

@@ -409,7 +409,7 @@ Applications can take advantage of S3 publish feature from DL Streamer Pipeline
    >NOTE- For sake of simplicity, we assume that the new model has already been downloaded by Model Download microservice. The following curl command is only a simulation that just downloads the model. In production, however, they will be downloaded by the Model Download service.
 
    ```sh
-   export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/1d40dfe1791d44e8cf6e8472c28c034e40fa508d/models/INT8/pallet_defect_detection.zip'
+   export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/06bb0d621cb14a1791672552a538beddddcc4066/models/INT8/pallet_defect_detection.zip'
 
    curl -L "$MODEL_URL" -o "$(basename $MODEL_URL)"
 

manufacturing-ai-suite/industrial-edge-insights-vision/docs/user-guide/weld-porosity/release-notes/march-2026.md

@@ -8,4 +8,5 @@
 - MLOps is now demonstrated with Model Download microservice instead of Model Registry
 - Removed Model Registry service and its references
 - NGINX,COTURN and MINIO ports made configurable as environment variables
-- Consumed latest DL Streamer Pipeline Server 2026.0.0 image. Ubuntu24 variant of the image is default now.
+- Consumed latest DL Streamer Pipeline Server 2026.0.0 image. Ubuntu24 variant of the image is default now.
+- Model changed from FP16 to INT8

manufacturing-ai-suite/industrial-edge-insights-vision/docs/user-guide/worker-safety-gear-detection/get-started/deploy-multiple-instances-with-helm.md

@@ -821,7 +821,7 @@ Applications can take advantage of S3 publish feature from DL Streamer Pipeline
    >NOTE- For sake of simplicity, we assume that the new model has already been downloaded by Model Download microservice. The following curl command is only a simulation that just downloads the model. In production, however, they will be downloaded by the Model Download service.
 
    ```sh
-    export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/1d40dfe1791d44e8cf6e8472c28c034e40fa508d/models/INT8/worker-safety-gear-detection.zip'
+    export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/06bb0d621cb14a1791672552a538beddddcc4066/models/INT8/worker-safety-gear-detection.zip'
 
     curl -L "$MODEL_URL" -o "$(basename $MODEL_URL)"
 

manufacturing-ai-suite/industrial-edge-insights-vision/docs/user-guide/worker-safety-gear-detection/get-started/deploy-with-helm.md

@@ -394,7 +394,7 @@ Applications can take advantage of S3 publish feature from DL Streamer Pipeline
    >NOTE- For sake of simplicity, we assume that the new model has already been downloaded by Model Download microservice. The following curl command is only a simulation that just downloads the model. In production, however, they will be downloaded by the Model Download service.
 
    ```sh
-   export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/1d40dfe1791d44e8cf6e8472c28c034e40fa508d/models/INT8/worker-safety-gear-detection.zip'
+   export MODEL_URL='https://github.com/open-edge-platform/edge-ai-resources/raw/06bb0d621cb14a1791672552a538beddddcc4066/models/INT8/worker-safety-gear-detection.zip'
 
    curl -L "$MODEL_URL" -o "$(basename $MODEL_URL)"