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Firstly, thanks to all of you for the bravo project!
Currently, the model seems like does not support int8 quantization. Any plan on it?
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1. Is the newly released 'TFLite Export with INT8 Quantization' only quantize the yolov8 backbone(or image encoder)? I note that you emphasis on 'Please use Reparameterized YOLO-World for TFLite!!' ,…
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I have used PTQ for int8 export from pytorch model and despite attempts at calibration, there is a significant drop in detection accuracy.
I am moving to quantization aware training to improve the…
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I would like to quantize my model to INT8 precision and then compile it using torch_tensorrt.
Unfortunately, it is [transformer based vision model](https://github.com/mit-han-lab/efficientvit/blob/ma…
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# Platform(Include target platform as well if cross-compiling):
aarch64, ubuntu20.04
# Github版本:
commit a980dba3963efb0ad76b0f3caaf5c21556f69ffe (HEAD -> master, origin/master, origin/HEAD)
…
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# Summary
* We (engineering at @neuralmagic) are working on support for int8 quantized activations.
* This RFC is proposing an _incremental_ approach to quantization, where the initial support for q…
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Hi everyone,
I’m working on a project that involves deploying a YOLOv10 model on a mobile/edge device. To improve inference speed and reduce the model size, I want to convert my YOLOv10 model to Te…
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Previously we do this
```python
from torchao.quantization.quant_api import change_linear_weights_to_int8_woqtensors
model = torch.compile(model, mode="max-autotune", fullgraph=True)
change_lin…
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### Search before asking
- [X] I have searched the YOLOv8 [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and fou…
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Are the int8 and int4 quantization mentioned in the paper open source and supported in this repo