https://terms-en.ai-term-hub.com/zh/tags/configuration/Recent content in Configuration on 中文AI术语词典Hugozh-cnSat, 18 Jul 2026 11:44:45 +0000https://terms-en.ai-term-hub.com/zh/terms/model_index/Sat, 18 Jul 2026 11:26:24 +0000https://terms-en.ai-term-hub.com/zh/terms/model_index/<h2 id="definition">Definition</h2> <p>索引文件（通常名为 &lsquo;model_index.json&rsquo;）包含有关模型架构的结构化信息，包括管道类型、子模型和配置路径。它使 Hub 能够正确协调多组件模型的加载。</p> <h3 id="summary">Summary</h3> <p>模型索引是 Hugging Face Hub 用于描述和组织模型组件及配置的元数据文件。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>元数据</li> <li>管道配置</li> <li>模型加载</li> <li>互操作性</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>定义多组件管道</li> <li>上传复杂模型到 Hub</li> <li>自动化模型发现与加载</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/config-json-%E9%85%8D%E7%BD%AE%E6%96%87%E4%BB%B6-json/">Config JSON (配置文件 JSON)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/pipeline-%E7%AE%A1%E9%81%93/">Pipeline (管道)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/hugging-face-hub-hugging-face-%E6%A8%A1%E5%9E%8B%E4%B8%AD%E5%BF%83/">Hugging Face Hub (Hugging Face 模型中心)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/serialization-%E5%BA%8F%E5%88%97%E5%8C%96/">Serialization (序列化)</a></li> </ul>https://terms-en.ai-term-hub.com/zh/terms/hyperparameter/Sat, 18 Jul 2026 11:21:34 +0000https://terms-en.ai-term-hub.com/zh/terms/hyperparameter/<h2 id="definition">Definition</h2> <p>与模型参数（权重和偏置）不同，后者是在训练过程中从数据中学习得到的，而超参数是实践者在训练开始前选择的外部设置。它们控制着模型的结构、学习过程以及正则化强度等关键方面。</p> <h3 id="summary">Summary</h3> <p>一种在训练过程之前设定其值的配置变量，用于控制学习算法的行为。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>学习率</li> <li>批次大小</li> <li>模型架构</li> <li>正则化</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>配置神经网络训练</li> <li>设置梯度下降步骤</li> <li>定义随机森林中的树深度</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/hyperparameter_tuning-%E8%B6%85%E5%8F%82%E6%95%B0%E8%B0%83%E4%BC%98/">hyperparameter_tuning (超参数调优)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/model_parameters-%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0/">model_parameters (模型参数)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/learning_rate-%E5%AD%A6%E4%B9%A0%E7%8E%87/">learning_rate (学习率)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/batch_size-%E6%89%B9%E6%AC%A1%E5%A4%A7%E5%B0%8F/">batch_size (批次大小)</a></li> </ul>https://terms-en.ai-term-hub.com/zh/terms/tuning/Sat, 18 Jul 2026 10:55:40 +0000https://terms-en.ai-term-hub.com/zh/terms/tuning/<h2 id="definition">Definition</h2> <p>调优涉及改进机器学习模型以实现更好的准确性或效率。它可以指超参数调优，即优化学习率或批次大小等设置；也可以指模型权重的微调。</p> <h3 id="summary">Summary</h3> <p>调整超参数或模型权重以优化特定数据集或任务性能的过程。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>超参数</li> <li>网格搜索</li> <li>随机搜索</li> <li>防止过拟合</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>优化模型准确性</li> <li>降低推理延迟</li> <li>使模型适应特定领域</li> </ul> <h2 id="code-example">Code Example</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#f92672">from</span> sklearn.model_selection <span style="color:#f92672">import</span> GridSearchCV </span></span><span style="display:flex;"><span>param_grid <span style="color:#f92672">=</span> {<span style="color:#e6db74">&#39;C&#39;</span>: [<span style="color:#ae81ff">0.1</span>, <span style="color:#ae81ff">1</span>, <span style="color:#ae81ff">10</span>]} </span></span><span style="display:flex;"><span>search <span style="color:#f92672">=</span> GridSearchCV(svm, param_grid, cv<span style="color:#f92672">=</span><span style="color:#ae81ff">5</span>) </span></span></code></pre></div><h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/hyperparameter_optimization-%E8%B6%85%E5%8F%82%E6%95%B0%E4%BC%98%E5%8C%96/">hyperparameter_optimization (超参数优化)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/grid_search-%E7%BD%91%E6%A0%BC%E6%90%9C%E7%B4%A2/">grid_search (网格搜索)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/fine_tuning-%E5%BE%AE%E8%B0%83/">fine_tuning (微调)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/validation-%E9%AA%8C%E8%AF%81/">validation (验证)</a></li> </ul>