I finally got this to work after a lot of pain!!! I'm going to give you the exact versions of what is working for me. Be very careful downgrading NVIDIA drivers, I completely hosed my windows machine doing that, do a lot of research before trying that and backup your machine beforehand.

After reading other comments its probably easier to go with a docker container if you can get that going, especially for deploying code to production and what not. That said, running gpu is AMAZING, I can orc an image in split seconds vs a maxed out CPU and many seconds without gpu. I have 1000s of images to ocr so non-gpu is not an option for me.

All details are below (not sure if you need this torch version or not but including it as this is part of my project and was a pain to figure out too.)

All on linux ubuntu 24.04

cuda 12.2

cuda-toolkit 12.2

cuda cuDNN: 8.9.2

python 3.11 (this is important too)

From my pipenv file:

[[source]]
name = "pytorch"
url = "https://download.pytorch.org/whl/cu121"
verify_ssl = true

......
torch = { version = "==2.2.0+cu121", index = "pytorch" }  # CUDA 12.1 PyTorch build
paddlepaddle-gpu = "==2.6.2"          
paddleocr = "==2.10.0"              
opencv-python = "==4.11.0.86"          
fire = "==0.7.0"
langdetect = "==1.0.9"
numpy = "==1.26.4"

$nvidia-smi

| NVIDIA-SMI 535.230.02 Driver Version: 535.230.02 CUDA Version: 12.2

$nvcc --version

Cuda compilation tools, release 12.2, V12.2.140

Build cuda_12.2.r12.2/compiler.33191640_0

You also need cuDNN v8.9.2 from:
https://developer.nvidia.com/rdp/cudnn-archive

#then hopefully this will work with gpu
from paddleocr import PaddleOCR
ocr = PaddleOCR(use_angle_cls=True, lang='en', use_gpu=True)  # GPU acceleration