/en/tags/faq/Recent content in FAQ on Mi&Bee BlogHugo -- gohugo.ioen蓝宝石的傻话Sat, 23 May 2026 00:00:00 +0000/en/posts/aihelper/yolo-faq/Sat, 23 May 2026 00:00:00 +0000/en/posts/aihelper/yolo-faq/<h2 id="environment-installation-issues">Environment Installation Issues</h2> <p><strong>Q1: CUDA not available, only using CPU?</strong></p> <p>First confirm your NVIDIA driver version supports the required CUDA version. A driver that is too old will make CUDA unavailable:</p> <div class="code-block-wrapper" data-lang="bash"> <div class="code-block-header"> <div class="code-block-meta"><span class="code-language">bash</span></div> <button class="copy-button" aria-label="Copy code"> <svg class="copy-icon" xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg> <svg class="check-icon" xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="20 6 9 17 4 12"/></svg> </button> </div> <div class="code-block-body"><div class="highlight"><div class="chroma"> <table class="lntable"><tr><td class="lntd"> <pre tabindex="0" class="chroma"><code><span class="lnt">1 </span><span class="lnt">2 </span><span class="lnt">3 </span><span class="lnt">4 </span><span class="lnt">5 </span><span class="lnt">6 </span></code></pre></td> <td class="lntd"> <pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl"><span class="c1"># Check driver version (Driver Version must be &gt;= minimum for target CUDA)</span> </span></span><span class="line"><span class="cl">nvidia-smi </span></span><span class="line"><span class="cl"><span class="c1"># Check CUDA toolkit version</span> </span></span><span class="line"><span class="cl">nvcc --version </span></span><span class="line"><span class="cl"><span class="c1"># Reinstall PyTorch with matching CUDA version</span> </span></span><span class="line"><span class="cl">pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu121</span></span></code></pre></td></tr></table> </div> </div></div> </div><p>If <code>nvidia-smi</code> shows a CUDA version but PyTorch still uses CPU, you have installed the CPU-only PyTorch build. Uninstall and reinstall with the <code>--index-url</code> flag for the correct CUDA version. For CUDA 11.8, replace <code>cu121</code> with <code>cu118</code> in the URL. Always use a conda or venv virtual environment to isolate PyTorch versions and avoid system-level conflicts.</p>