Comments (2)
Actually, for is the only way to convert to an earlier version to downgrade the python conversion tool to an earlier version I think this covers it -
If you are building ONNX Runtime from source (custom, reduced or minimal builds), you must match the python package version to the branch of the ONNX Runtime repository you checked out.
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We don't generally support forwards compatibility. v6 was introduced in ORT 1.16.0 so the minimum version you would be able to use a v6 model in is 1.16.0.
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Related Issues (20)
- DML incorrect results, probably Split node HOT 2
- Build onnxruntime with SNPE EP on SA8155P HOT 1
- [E:onnxruntime:, sequential_executor.cc:516 onnxruntime::ExecuteKernel] Non-zero status code returned while running LayerNormalization node. HOT 2
- Run all Nodes on GPU/DML with DML-EP HOT 2
- ImportError: A dynamic link library (DLL) initialization routine failed after building source with Visual Studio 17.10 HOT 8
- [Mobile] onnxruntime-objc crash HOT 4
- v1.17.0 + requires macOS deployment target >= than 13.3 due to C++ 20 HOT 9
- Non-zero status code returned while running ConvTranspose node.
- [Documentation] Install page missing instructions for onnxruntime-rocm HOT 2
- onnxruntime shape mismatch during quantization of yolov8 models HOT 6
- CUDA wasnt able to be loaded when tring to use CUDA12.4 and onnxruntime-gpu 11.8 HOT 2
- Flan-T5 small converted model produces wrong result with batch size > 1 and long senetences
- [Training] Support for RKNPU Execution Provider on RK3562 Platform and On-Device Training Capabilities HOT 1
- Support Numpy v2.0 HOT 9
- Segmentation fault during inference HOT 2
- Can't find definition of OrtTensorRTProviderOptionsV2 in latest release
- [Mobile] Segmentation fault after repeated inference HOT 5
- [Bug] W16A16 quantization, qdq_error is empty, but W8A8 is normal HOT 1
- [Feature Request] support FP8 calibraion method and quantization HOT 2
- DML cannot use device_id = 1 , run_with_iobinding failed. HOT 1
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