Comments (1)
@GLOMQuyet thank you for the model request! I have added it to our list of models to add in the future.
In the meantime, feel free to follow the BYOM (Bring Your Own Model) path and submit this model to Hub. If there are any issues in getting a successful and/or performant job on Hub. Feel free to let us know on slack in #performance-help.
You can follow these instructions to submit your Torch model on Hub: https://app.aihub.qualcomm.com/docs/hub/profile_examples.html#profiling-a-pytorch-model
from ai-hub-models.
Related Issues (20)
- Execute quantized model on TFLite with QCS6490 HOT 1
- [BUG] Model with element-wise select / torch.where() fails to finalize HOT 1
- Performance issue HOT 1
- How to quantize LLM to INT4? HOT 5
- apps/android Building Android APP failed HOT 6
- No such file or directory: '/opt/qcom/aistack/qairt/2.21.0.240401/lib/android/qtld-release.aar' HOT 10
- Image_Classification apk is crashed after device runtime is selected HOT 1
- [BUG] Controlnet models are providing noisy image outputs HOT 1
- [BUG] Improvements for apps/Android/ImageClassification/build_apk.py HOT 2
- [Feature Request] Additional Profiling Statistics HOT 1
- Label.txt file for yolov8_det.tflite model HOT 1
- [Feature Request] ControlNet app sample HOT 2
- [BUG] ModuleNotFoundError: No module named 'ffnet_datasets' HOT 1
- [Feature Request] Linux on ARM HOT 5
- Incorrect Comment HOT 1
- pacakage error HOT 2
- import com.qualcomm2.QnnDelegate fail HOT 1
- Using NPU in ImageClassification demo app HOT 2
- dynamic dimension shape input HOT 1
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