Comments (2)
Better APIs for hookups to android and IOS apps are on the roadmap.
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I'm also very interested in deploying models with Flutter.
from executorch.
Related Issues (20)
- How to analyze executorch .pte file performance? HOT 6
- Operator torch._ops.quantized_decomposed.quantize_per_tensor.default is not Aten Canonical HOT 4
- Move Arm bare-metal platform builds to C++17, and include arm builds and aot flow in standard precommits HOT 1
- ’xnn_executor_runner' is missing in the documentation 'Building and Running ExecuTorch with XNNPACK Backend'
- Unknown target `generated_lib_all_ops` from package `root//kernels/portable`.
- The core has been dumped after alternately reasoning three times about the two preloaded models
- ExecuTorch main branch setup fails while stable branch works HOT 4
- nn.BatchNorm2d is not supported at exir.to_edge HOT 9
- How to perform inference and gathering accuracy metrics on executorch model
- For the Runtime build for QNN
- Fix flaky test TestQuantLoweringCustomBackendPass
- ModuleNotFoundError: No module named 'executorch.extension.pytree.pybindings' HOT 5
- Magic header does not match the expected version.
- pThread Link error - run Llama model.
- dummy_llama compile error for qnn backend: TypeError: expected str, bytes or os.PathLike object, not NoneType HOT 6
- QNN: huge accuracy degradation in 16a4w quantization HOT 2
- Properly address dependency to torchao
- Can't run examples ExecuTorch HOT 3
- error: Variable `typing` not found while building the runtime HOT 3
- no attribute 'dequantize_per_channel_group'. Did you mean: 'dequantize_per_channel'? HOT 5
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