Comments (2)
I hate GitHub's assets because it's super slow. That's why I go to the trouble of placing my resources in external storage in the US Region, even though I live in Asia.
I don't know what causes the error. Btw, I just accessed the URL directly with wget and curl and the file downloaded fine.
I know that operationally Assets
are very useful. I also know that S3 can be unstable from region to region. "Wasabi Storage," a paid storage facility, has recently been reported unstable in other repositories. There is nothing I can do about the instability of the external vendor storage I have contracted with.
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@PINTO0309 yeah it's very strange that the download fails sometimes. I'm in Spain but I assume the CI runs from US servers, and I can download the file myself manually fine also. It will probably clear up again if we wait some time, but I thought the GitHub assets idea might be more stable because we use them for almost everything (including YOLOv8 model and dataset auto-download) and have never really had any issues over the last few years.
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Related Issues (20)
- "GEMM: Dimension mismatch" during value validation phase HOT 4
- Exclude selected operations from INT8 quantized model HOT 18
- ValueError in MaxPool Layer during ONNX to TensorFlow Conversion with 3D Input HOT 5
- The tflite detection result converted from the yolo NAS model is inaccurate. HOT 5
- Converting quantized onnx with Q/DQ representation to full int8 TFLite model HOT 2
- Unable to replace flatten HOT 4
- How to convert onnx(NCHW) to NHWC and write back to onnx file Because my HW takes onnx file as input in NHWC format HOT 3
- How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file HOT 1
- How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file HOT 3
- Please do reply for the last time either this issue or @ How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file #586 HOT 1
- ONNX Split operation converts to a tf StridedSlice operation with outputs in the wrong order. HOT 2
- Depth_Anything to ONNX model's conversion failed HOT 1
- Bad accuracy after conversion HOT 1
- onnx2tf conversion error for gpt2 transformers model HOT 2
- onnx2tf conversion error for gpt2 transformers model #591 follow up HOT 2
- Error when trying to run converted model; gpt2 tensorflow from onnx #591 follow up HOT 1
- Modifying Multi-output Layer index when Exporting onnx to tflite HOT 1
- Model modification issue HOT 2
- Onnx to tflite conversion issue on TILE layer.
- While converting onnx to tflite TILE layer is getting ignored. HOT 2
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