mirror of
https://github.com/RootKit-Org/AI-Aimbot.git
synced 2025-06-21 02:41:01 +08:00
Update README.md
This commit is contained in:
parent
be14306b3f
commit
25a411b676
15
README.md
15
README.md
@ -92,29 +92,32 @@ Follow these sparkly steps to get your TensorRT ready for action! 🛠️✨
|
||||
5. **CUDNN Installation** 🧩
|
||||
Click to install [CUDNN 📥](https://developer.nvidia.com/downloads/compute/cudnn/secure/8.9.6/local_installers/11.x/cudnn-windows-x86_64-8.9.6.50_cuda11-archive.zip/). You'll need a Nvidia account to proceed. Don't worry it's free.
|
||||
|
||||
6. **Get TensorRT 8.6 GA** 🔽
|
||||
6. **Unzip and Relocate** 📁➡️
|
||||
Open the .zip CuDNN file and move all the folders/files to where the CUDA Toolkit is on your machine, usually at `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8`.
|
||||
|
||||
7. **Get TensorRT 8.6 GA** 🔽
|
||||
Fetch [`TensorRT 8.6 GA 🛒`](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/secure/8.6.1/zip/TensorRT-8.6.1.6.Windows10.x86_64.cuda-11.8.zip).
|
||||
|
||||
7. **Unzip and Relocate** 📁➡️
|
||||
8. **Unzip and Relocate** 📁➡️
|
||||
Open the .zip TensorRT file and move all the folders/files to where the CUDA Toolkit is on your machine, usually at `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8`.
|
||||
|
||||
8. **Python TensorRT Installation** 🎡
|
||||
9. **Python TensorRT Installation** 🎡
|
||||
Once you have all the files copied over, you should have a folder at `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python`. If you do, good, then run the following command to install TensorRT in python.
|
||||
```
|
||||
pip install "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python\tensorrt-8.6.1-cp311-none-win_amd64.whl"
|
||||
```
|
||||
🚨 If the following steps didn't work, don't stress out! 😅 The labeling of the files corresponds with the Python version you have installed on your machine. We're not looking for the 'lean' or 'dispatch' versions. 🔍 Just locate the correct file and replace the path with your new one. 🔄 You've got this! 💪
|
||||
|
||||
9. **Set Your Environmental Variables** 🌎
|
||||
10. **Set Your Environmental Variables** 🌎
|
||||
Add these paths to your environment:
|
||||
- `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib`
|
||||
- `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\libnvvp`
|
||||
- `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin`
|
||||
|
||||
10. **Download Pre-trained Models** 🤖
|
||||
11. **Download Pre-trained Models** 🤖
|
||||
You can use one of the .engine models we supply. But if it doesn't work, then you will need to re-export it. Grab the `.pt` file here for the model you want. We recommend `yolov5s.py` or `yolov5m.py` [HERE 🔗](https://github.com/ultralytics/yolov5/releases/tag/v7.0).
|
||||
|
||||
11. **Run the Export Script** 🏃♂️💻
|
||||
12. **Run the Export Script** 🏃♂️💻
|
||||
Time to execute `export.py` with the following command. Patience is key; it might look frozen, but it's just concentrating hard! Can take up to 20 mintues.
|
||||
|
||||
```
|
||||
|
Loading…
x
Reference in New Issue
Block a user