Expired50% confidenceSolutionExact time
The tutorial chose to install the relatively stable PyTorch version 1.13.1, and the core principle for installing PyTorch is that the CUDA version must match the GPU driver.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/25/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/23/2026(expired)
Sources
YOLOv8环境搭建完整指南：从Miniconda到Ultralytics安装
Related Claims
UnverifiedNVIDIA 10/20-series GPUs should use CUDA 12.4, while 30/40/50-series GPUs should use CUDA 13.69% similarUnverifiedCUDA 12.4 requires an NVIDIA driver version ≥ 550.54.65% similarUnverifiedPyTorch installed via pip install -r requirements.txt is the CPU version by default; to enable GPU acceleration, you must manually reinstall the GPU version of PyTorch corresponding to the appropriate CUDA version.65% similarUnverifiedThe torch and torchvision specified in requirements.txt are usually CPU versions; if GPU acceleration is needed, the GPU version of PyTorch corresponding to the CUDA version must be reinstalled manually.62% similarUnverifiedRunning nvidia-smi in the command line displays the maximum CUDA version supported by the installed driver61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/613396API
curl https://kongchang.com/api/v1/knowledge/claims/613396MCP
get_claim(id=613396)