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+model_farm_mask2former_qcs6490_qnn2.31_int8_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_mask2former_qcs6490_qnn2.31_w8a16_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_mask2former_qcs8550_qnn2.31_fp16_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_mask2former_qcs8550_qnn2.31_int8_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text
+model_farm_mask2former_qcs8550_qnn2.31_w8a16_aidlite/python/bus.jpg filter=lfs diff=lfs merge=lfs -text

model_farm_mask2former_qcs6490_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,384,384]
+- Number of parameters: 42.01M
+- Model size: 201M
+- Output shape: [[1,100,134],[1,100,96,96]]
+
+Source model repository: [Mask2Former](https://github.com/huggingface/transformers/tree/main/src/transformers/models/mask2former)
+
+### 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_mask2former_qcs6490_qnn2.31_int8_aidlite/models/Mask2Former_w8a8.qnn231.ctx.bin

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model_farm_mask2former_qcs6490_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,384,384]
+- Number of parameters: 42.01M
+- Model size: 201M
+- Output shape: [[1,100,134],[1,100,96,96]]
+
+Source model repository: [Mask2Former](https://github.com/huggingface/transformers/tree/main/src/transformers/models/mask2former)
+
+### 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_mask2former_qcs6490_qnn2.31_w8a16_aidlite/models/Mask2Former_w8a16.qnn231.ctx.bin

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model_farm_mask2former_qcs8550_qnn2.31_fp16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,384,384]
+- Number of parameters: 42.01M
+- Model size: 201M
+- Output shape: [[1,100,134],[1,100,96,96]]
+
+Source model repository: [Mask2Former](https://github.com/huggingface/transformers/tree/main/src/transformers/models/mask2former)
+
+### 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_mask2former_qcs8550_qnn2.31_fp16_aidlite/converted_models/Mask2Former_fp16.qnn231.ctx.bin

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+size 121160112

model_farm_mask2former_qcs8550_qnn2.31_int8_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,384,384]
+- Number of parameters: 42.01M
+- Model size: 201M
+- Output shape: [[1,100,134],[1,100,96,96]]
+
+Source model repository: [Mask2Former](https://github.com/huggingface/transformers/tree/main/src/transformers/models/mask2former)
+
+### 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_mask2former_qcs8550_qnn2.31_int8_aidlite/models/Mask2Former_w8a8.qnn231.ctx.bin

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model_farm_mask2former_qcs8550_qnn2.31_w8a16_aidlite/README.md

@@ -0,0 +1,40 @@
+## Model Information
+
+### Source model
+- Input shape: [1,3,384,384]
+- Number of parameters: 42.01M
+- Model size: 201M
+- Output shape: [[1,100,134],[1,100,96,96]]
+
+Source model repository: [Mask2Former](https://github.com/huggingface/transformers/tree/main/src/transformers/models/mask2former)
+
+### 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_mask2former_qcs8550_qnn2.31_w8a16_aidlite/models/Mask2Former_w8a16.qnn231.ctx.bin

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