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@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model_farm_face_attrib_net_qcs6490_qnn2.31_int8_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_face_attrib_net_qcs6490_qnn2.31_w8a16_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_face_attrib_net_qcs8550_qnn2.31_fp16_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_face_attrib_net_qcs8550_qnn2.31_int8_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_face_attrib_net_qcs8550_qnn2.31_w8a16_aidlite/python/test.jpg filter=lfs diff=lfs merge=lfs -text

model_farm_face_attrib_net_qcs6490_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x128x128]
+- Number of parameters: 11.58M
+- Model size: 46.35M
+- Output shape: [[1x512],[1x32],[1x2],[1x2],[1x2],[1x2]]
+
+Source model repository: [Face_Attrib_Net](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/face_attrib_net/model.py)
+
+### Converted model
+
+- Precision: INT8
+- Backend: QNN2.31
+- Target Device: FV01 QCS6490
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_face_attrib_net_qcs6490_qnn2.31_int8_aidlite/models/face_attrib_net_w8a8.qnn231.ctx.bin

@@ -0,0 +1,3 @@
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+oid sha256:895de1a5c9a1a975edcbe3048ef769c48720e6c5542e6d935d37c3e0f174df37
+size 13204488

model_farm_face_attrib_net_qcs6490_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x128x128]
+- Number of parameters: 11.58M
+- Model size: 46.35M
+- Output shape: [[1x512],[1x32],[1x2],[1x2],[1x2],[1x2]]
+
+Source model repository: [Face_Attrib_Net](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/face_attrib_net/model.py)
+
+### Converted model
+
+- Precision: W8A16
+- Backend: QNN2.31
+- Target Device: FV01 QCS6490
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_face_attrib_net_qcs6490_qnn2.31_w8a16_aidlite/models/face_attrib_net_w8a16.qnn231.ctx.bin

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+size 13257800

model_farm_face_attrib_net_qcs8550_qnn2.31_fp16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x128x128]
+- Number of parameters: 11.58M
+- Model size: 46.35M
+- Output shape: [[1x512],[1x32],[1x2],[1x2],[1x2],[1x2]]
+
+Source model repository: [Face_Attrib_Net](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/face_attrib_net/model.py)
+
+### Converted model
+
+- Precision: FP16
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_face_attrib_net_qcs8550_qnn2.31_fp16_aidlite/models/face_attrib_net_fp16.qnn231.ctx.bin

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+size 25938880

model_farm_face_attrib_net_qcs8550_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x128x128]
+- Number of parameters: 11.58M
+- Model size: 46.35M
+- Output shape: [[1x512],[1x32],[1x2],[1x2],[1x2],[1x2]]
+
+Source model repository: [Face_Attrib_Net](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/face_attrib_net/model.py)
+
+### Converted model
+
+- Precision: INT8
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_face_attrib_net_qcs8550_qnn2.31_int8_aidlite/models/face_attrib_net_w8a8.qnn231.ctx.bin

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+size 13229064

model_farm_face_attrib_net_qcs8550_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1x3x128x128]
+- Number of parameters: 11.58M
+- Model size: 46.35M
+- Output shape: [[1x512],[1x32],[1x2],[1x2],[1x2],[1x2]]
+
+Source model repository: [Face_Attrib_Net](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/face_attrib_net/model.py)
+
+### Converted model
+
+- Precision: W8A16
+- Backend: QNN2.31
+- Target Device: SNM972 QCS8550
+
+## Inference with AidLite SDK
+
+### SDK installation
+Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the [AidLite Developer Documentation](https://v2.docs.aidlux.com/en/sdk-api/aidlite-sdk/)
+
+- Install AidLite SDK
+
+```bash
+# Install the appropriate version of the aidlite sdk
+sudo aid-pkg update
+sudo aid-pkg install aidlite-sdk
+# Download the qnn version that matches the above backend. Eg Install QNN2.23 Aidlite: sudo aid-pkg install aidlite-qnn223
+sudo aid-pkg install aidlite-{QNN VERSION}
+```
+
+- Verify AidLite SDK
+
+```bash
+# aidlite sdk c++ check
+python3 -c "import aidlite ; print(aidlite.get_library_version())"
+
+# aidlite sdk python check
+python3 -c "import aidlite ; print(aidlite.get_py_library_version())"
+```

model_farm_face_attrib_net_qcs8550_qnn2.31_w8a16_aidlite/models/face_attrib_net_w8a16.qnn231.ctx.bin

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+version https://git-lfs.github.com/spec/v1
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+size 13474824