-
I have a cluster with 3 machines:
* Ubuntu Linux 22.04 with 32GB RAM + Quadro RTX 4000
* Ubuntu Linux 22.04 with 64GB RAM + Quadro RTX 5000
* M2 MacOS 14.7 with 32GB of RAM
_I still couldn…
-
`from ultralytics import YOLO
import cv2
model_path = r"C:/Users/10124/Desktop/yolov9/yolov9-main/runs/train/exp17/weights/best.pt"
model = YOLO(model_path)
cap = cv2.VideoCapture(video)
ret, f…
-
### Motivation
The onnxruntime inference engine supports the rocm environment, but can mmdeploy also support it?
### Related resources
_No response_
### Additional context
_No response_
-
Hi,
I remember the support on vLLM was on your TODOs. Have you achieved it now? Was the main challenge in this direction that the batch size > 1 tree verification is hard to made efficient? Thanks…
-
Hi Zhifeng,
Thank you so much for your help!
This issue is related to https://github.com/NVIDIA/audio-flamingo/issues/5, https://github.com/NVIDIA/audio-flamingo/issues/6, https://github.com/NVI…
-
## Use case
Following up on #6805
It would be useful to be able to create custom suggestions in the platform, rather than asking the OpenCTI developers to include new ones on a case by case basi…
-
Has the emulator engine to be part of the platform itself?
The practical workflow will be that you have an RT model and calibrate an GP emulator based on that. The calibrated emulator is then used fo…
-
我尝试了 PP-YOLOE_plus-L和YOLOX-L模型，可以正常导出ONNX，但是加载运行时报错
Op (Gather) [ShapeInferenceError] data tensor must have rank >= 1"
尝试多个方法都无法解决这个问题，也有其他人提了同个issuse，如下：
https://github.com/PaddlePaddle/Paddle2O…
-
It seems a bit unfair to file this as a "bug," when really what's going on is that the Python community is trying to figure out what a "typed" Python library looks like. In this case, what looks like …
-
When I increase batch size, the inference time on TensorRT does not change. Basically if inference time on the batch with size 8 took 20ms. Inference on batch size 16 just takes 40ms. I am not sure wh…