import{s as pt,f as He,n as rt,o as it}from"../chunks/scheduler.37c15a92.js";import{S as mt,i as ct,g as o,s as a,r as d,A as ut,h as p,f as l,c as n,j as O,u as w,x as i,k as r,y as dt,a as s,v as f,d as y,t as h,w as J}from"../chunks/index.2bf4358c.js";import{C as A}from"../chunks/CodeBlock.4e987730.js";import{D as wt}from"../chunks/DocNotebookDropdown.efc1fb7c.js";import{H as ot,E as ft}from"../chunks/getInferenceSnippets.80a69898.js";function yt(Ve){let M,ee,D,te,b,le,T,se,g,Xe="让我们从安装 Gradio 开始吧！与安装其他 Python 包一样，只需运行：",ae,j,ne,U,Qe="Gradio 支持所有常见的平台，无论是从你最喜欢的 Python IDE、Jupyter notebook 还是 Google Colab 🤯！",oe,x,Pe="所以无论你在哪里运行 Python，都可以安装 Gradio！",pe,$,Re="让我们从一个简单的“Hello World”示例开始熟悉 Gradio 语法：",re,G,ie,k,qe="让我们逐步解释上面的代码：",me,I,Se="<li>首先，我们定义一个名为 <code>greet()</code> 的函数。在这个例子中，它是一个在你的名字前添加“Hello”的简单函数，不过它可以被替换为任意的 Python 函数。例如，在机器学习的演示中，该函数可以调用机器学习模型对输入进行预测并返回输出。</li> <li>然后，我们创建一个带有三个参数 <code>fn</code> 、 <code>inputs</code> 和 <code>outputs</code> 的 Gradio <code>Interface</code> 。这些参数定义了预测函数，以及我们想要的输入和输出组件的类型。在我们的这个例子中，输入和输出组件都是简单的文本框。</li> <li>最后我们调用创建的 <code>Interface</code> 上的 <code>launch()</code> 方法。</li>",ce,C,Ye='如果你运行这段代码，下面的界面会自动出现在 Jupyter/Colab notebook 中，或者如果在一个脚本中运行，会自动在浏览器中弹出 <strong><a href="http://localhost:7860" rel="nofollow">http://localhost:7860</a></strong> 。',ue,m,Fe,de,v,ze="现在，试着使用你自己的名字或其他的输入来试一试这个 GUI！",we,B,Ee="你会注意到，在这个 GUI 中，在这个例子中，Gradio 会根据输入参数的名称（<code>name</code>）自动推断文本框顶部的标签。如果你想改变这个标签怎么办？或者，如果你想自定义这个文本框的其他属性？在这种情况下，你可以实例化一个表示输入组件的类。",fe,Z,Le="看看下面的例子：",ye,W,he,c,Ne,Je,_,Ae="在上面的代码中，我们创建了一个带有自定义标签、预设的占位符和固定行数的输入文本框。同时，你也可以自定义输出文本框，但我们现在先不管它。",Me,H,De="我们已经看到，只需几行代码，Gradio 就能让你围绕任何函数创建一个简单的界面，同时兼容各种类型的输入或输出。在本节中，我们先从一个简单的文本框开始，但在接下来的节中，我们将介绍其他类型的输入和输出。现在让我们看一下如何在 Gradio 应用中包含一些自然语言处理（NLP）模型。",be,V,Te,X,Ke="现在让我们构建一个简单的界面，让你可以在这个界面中演示像 GPT-2 这样的<strong>文本生成</strong>模型。",ge,Q,Oe=`我们将使用 🤗 Transformers 中的 <code>pipeline()</code> 函数加载我们的模型。
如果你需要快速复习，你可以返回到 <a href="/course/chapter1/3#text-generation">第一章</a> 进行回顾。`,je,P,et="首先，我们定义一个预测函数，它接收一个文本输入并返回文本生成的结果：",Ue,R,xe,q,tt="此函数会不断接龙补全输入，你可以自己尝试各种输入来查看它是如何运行的。下面是一个示例（你可能会得到不同的输出结果）：",$e,S,Ge,Y,ke,F,lt="现在我们有了一个生成预测的函数，接下来可以像之前一样创建和启动一个 <code>Interface</code> ：",Ie,z,Ce,E,st="就是这样！你现在可以在 Interface 创建的 Web 网页上使用 GPT-2 模型生成文本，如下所示 🤯：",ve,u,at,Be,L,nt="接下来，让我们一起了解一下如何使用 Gradio 构建其他输入输出类型的演示！",Ze,N,We,K,_e;return b=new ot({props:{title:"构建你的第一个演示",local:"构建你的第一个演示",headingTag:"h1"}}),T=new wt({props:{classNames:"absolute z-10 right-0 top-0",options:[{label:"Google Colab",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/chapter9/section2.ipynb"},{label:"Aws Studio",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/master/course/chapter9/section2.ipynb"}]}}),j=new A({props:{code:"cGlwJTIwaW5zdGFsbCUyMGdyYWRpbyUwQQ==",highlighted:`pip install gradio
`,wrap:!1}}),G=new A({props:{code:"aW1wb3J0JTIwZ3JhZGlvJTIwYXMlMjBnciUwQSUwQSUwQWRlZiUyMGdyZWV0KG5hbWUpJTNBJTBBJTIwJTIwJTIwJTIwcmV0dXJuJTIwJTIySGVsbG8lMjAlMjIlMjAlMkIlMjBuYW1lJTBBJTBBJTBBZGVtbyUyMCUzRCUyMGdyLkludGVyZmFjZShmbiUzRGdyZWV0JTJDJTIwaW5wdXRzJTNEJTIydGV4dCUyMiUyQyUyMG91dHB1dHMlM0QlMjJ0ZXh0JTIyKSUwQSUwQWRlbW8ubGF1bmNoKCk=",highlighted:`<span class="hljs-keyword">import</span> gradio <span class="hljs-keyword">as</span> gr


<span class="hljs-keyword">def</span> <span class="hljs-title function_">greet</span>(<span class="hljs-params">name</span>):
    <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;Hello &quot;</span> + name


demo = gr.Interface(fn=greet, inputs=<span class="hljs-string">&quot;text&quot;</span>, outputs=<span class="hljs-string">&quot;text&quot;</span>)

demo.launch()`,wrap:!1}}),W=new A({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> gradio <span class="hljs-keyword">as</span> gr


<span class="hljs-keyword">def</span> <span class="hljs-title function_">greet</span>(<span class="hljs-params">name</span>):
    <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;Hello &quot;</span> + name


<span class="hljs-comment"># 我们将文本框类实例化</span>
textbox = gr.Textbox(label=<span class="hljs-string">&quot;Type your name here:&quot;</span>, placeholder=<span class="hljs-string">&quot;John Doe&quot;</span>, lines=<span class="hljs-number">2</span>)

gr.Interface(fn=greet, inputs=textbox, outputs=<span class="hljs-string">&quot;text&quot;</span>).launch()`,wrap:!1}}),V=new ot({props:{title:"🤖 使用模型预测",local:"🤖 使用模型预测",headingTag:"h2"}}),R=new A({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMHBpcGVsaW5lJTBBJTBBbW9kZWwlMjAlM0QlMjBwaXBlbGluZSglMjJ0ZXh0LWdlbmVyYXRpb24lMjIpJTBBJTBBJTBBZGVmJTIwcHJlZGljdChwcm9tcHQpJTNBJTBBJTIwJTIwJTIwJTIwY29tcGxldGlvbiUyMCUzRCUyMG1vZGVsKHByb21wdCklNUIwJTVEJTVCJTIyZ2VuZXJhdGVkX3RleHQlMjIlNUQlMEElMjAlMjAlMjAlMjByZXR1cm4lMjBjb21wbGV0aW9u",highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

model = pipeline(<span class="hljs-string">&quot;text-generation&quot;</span>)


<span class="hljs-keyword">def</span> <span class="hljs-title function_">predict</span>(<span class="hljs-params">prompt</span>):
    completion = model(prompt)[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;generated_text&quot;</span>]
    <span class="hljs-keyword">return</span> completion`,wrap:!1}}),S=new A({props:{code:"cHJlZGljdCglMjJNeSUyMGZhdm9yaXRlJTIwcHJvZ3JhbW1pbmclMjBsYW5ndWFnZSUyMGlzJTIyKQ==",highlighted:'<span class="hljs-function"><span class="hljs-title">predict</span><span class="hljs-params">(<span class="hljs-string">&quot;My favorite programming language is&quot;</span>)</span></span>',wrap:!1}}),Y=new A({props:{code:"JTNFJTNFJTIwTXklMjBmYXZvcml0ZSUyMHByb2dyYW1taW5nJTIwbGFuZ3VhZ2UlMjBpcyUyMEhhc2tlbGwuJTIwSSUyMHJlYWxseSUyMGVuam95ZWQlMjB0aGUlMjBIYXNrZWxsJTIwbGFuZ3VhZ2UlMkMlMjBidXQlMjBpdCUyMGRvZXNuJ3QlMjBoYXZlJTIwYWxsJTIwdGhlJTIwZmVhdHVyZXMlMjB0aGF0JTIwY2FuJTIwYmUlMjBhcHBsaWVkJTIwdG8lMjBhbnklMjBvdGhlciUyMGxhbmd1YWdlLiUyMEZvciUyMGV4YW1wbGUlMkMlMjBhbGwlMjBpdCUyMGRvZXMlMjBpcyUyMGNvbXBpbGUlMjB0byUyMGElMjBieXRlJTIwYXJyYXku",highlighted:'&gt;&gt; My favorite programming language <span class="hljs-keyword">is</span> Haskell. I really enjoyed <span class="hljs-keyword">the</span> Haskell language, <span class="hljs-keyword">but</span> <span class="hljs-keyword">it</span> doesn&#x27;t have all <span class="hljs-keyword">the</span> features <span class="hljs-keyword">that</span> can be applied <span class="hljs-keyword">to</span> any other language. For example, all <span class="hljs-keyword">it</span> <span class="hljs-keyword">does</span> <span class="hljs-keyword">is</span> compile <span class="hljs-keyword">to</span> a byte array.',wrap:!1}}),z=new A({props:{code:"aW1wb3J0JTIwZ3JhZGlvJTIwYXMlMjBnciUwQSUwQWdyLkludGVyZmFjZShmbiUzRHByZWRpY3QlMkMlMjBpbnB1dHMlM0QlMjJ0ZXh0JTIyJTJDJTIwb3V0cHV0cyUzRCUyMnRleHQlMjIpLmxhdW5jaCgp",highlighted:`<span class="hljs-keyword">import</span> gradio <span class="hljs-keyword">as</span> gr

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