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<h1 id="">簡介</h1>
<p>歡迎來到Hugging Face的教學！本篇介紹將會帶著你設置運行環境。如果你正開始學的話，不妨先看看<a href="/course/chapter1">第一章</a>再回來，這樣就能直接開始試著執行裡面的程式碼了。</p>
<p>我們會用到的所有函式庫都將會以Python資源包的方式被取得，所以這邊我們會教你如何設置Python環境並安裝你所需要的函式庫。</p>
<p>本篇將會涵蓋兩種設置環境的方法 - 使用Colab notebook或是Python虛擬環境。選你自己覺得合適的方式就好，但是對於初學者我們強烈推薦先從使用Colab notebook開始。</p>
<p>我們不會提到Windows系統，如果你是Windows的使用者，我們建議使用Colab notebook。如果你用的是Linux或是macOS，你可以任意選擇上述的兩種方法。</p>
<p>大部分的教學都會需要一個Hugging Face的帳號。我們建議現在就<a href="https://huggingface.co/join" rel="nofollow">創一個</a>。</p>
<h2 class="relative group"><a id="google-colab-notebook" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#google-colab-notebook"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>使用Google Colab notebook
	</span></h2>

<p>用Colab notebook是最簡單容易的方法；在瀏覽器開一頁Colab notebook就能直接開始寫程式了！</p>
<p>如果你對Colab notebook不熟悉的話，我們建議你從<a href="https://colab.research.google.com/notebooks/intro.ipynb" rel="nofollow">這篇介紹</a>開始。在Colab上你可以使用一些加速硬體，像是GPU或TPU，而且工作量不大的話也不收錢。</p>
<p>當你開始熟悉Colab後，建立新的筆記本然後開始進行設置：</p>
<div class="flex justify-center"><img src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter0/new_colab.png" alt="An empty colab notebook" width="80%"></div>
<p>接下來就是安裝我們將會用到的函式庫。我們會使用 <code>pip</code> 這個Python的資源管理工具來安裝。在Colab notebook裡，你可以用 <code>!</code> 來執行系統指令，所以你可以用以下的指令來安裝 🤗 Transformers函式庫：</p>

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	<pre><!-- HTML_TAG_START -->!pip <span class="hljs-keyword">install</span> transformers<!-- HTML_TAG_END --></pre></div>
<p>把函式庫導入到Python runtime可以確認你的資源包有被正確地安裝：</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">import</span> transformers<!-- HTML_TAG_END --></pre></div>
<div class="flex justify-center"><img src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter0/install.gif" alt="A gif showing the result of the two commands above: installation and import" width="80%"></div>
<p>這會安裝一個非常輕量的🤗 Transformers。裡面沒有安裝任何像是PyTorch或TensorFlow等的機器學習框架。因為我們會用到很多函式庫裡的不同功能，所以我們建議安裝包含了大部分使用情境所需資源的開發用版本：</p>

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	<pre><!-- HTML_TAG_START -->!pip <span class="hljs-keyword">install</span> transformers[sentencepiece]<!-- HTML_TAG_END --></pre></div>
<p>這會花一點時間，不過裝完你就已經完全準備好面對剩下的教學了！</p>
<h2 class="relative group"><a id="python" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#python"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>使用Python虛擬環境
	</span></h2>

<p>如果你比較想用Python虛擬環境的話，第一步就是安裝Python。我們建議跟著<a href="https://realpython.com/installing-python/" rel="nofollow">這篇教學</a>做為起手式。</p>
<p>當你安裝好Python後，你應該就能從終端機執行Python指令了。在進行下一步之前你可以先執行以下指令來確認Python有沒有安裝好：<code>python --version</code> 這條指令會讓終端機顯示你所安裝的Python版本。</p>
<p>在終端機執行像是<code>python --version</code>的Python指令時，你應該把你的指令想成是用你系統上主要的Python版本來執行。我們建議不要在這個版本上安裝任何資源包，讓每個專案在各自獨立的環境裡運行就可以了。這樣每個專案都可以有各自的相依性跟資源包，你也不用擔心不同專案之間使用同一個環境時潛在的相容性問題。</p>
<p>在Python我們可以用<a href="https://docs.python.org/3/tutorial/venv.html" rel="nofollow"><em>虛擬環境</em></a>來做這件事。虛擬環境是一個獨立包裝的樹狀目錄，每一個目錄下都有安裝特定版本的Python跟它需要的所有資源包。創建這樣的虛擬環境可以用很多不同的工具，不過我們會用一個叫做<a href="https://docs.python.org/3/library/venv.html#module-venv" rel="nofollow"><code>venv</code></a>的Python官方資源包。</p>
<p>首先，創建你希望你的程式執行時所在的目錄 - 舉例來說，你可能想要在你的家目錄下新增一個叫<em>transformers-course</em>的目錄：</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-built_in">mkdir</span> ~/transformers-course
<span class="hljs-built_in">cd</span> ~/transformers-course<!-- HTML_TAG_END --></pre></div>
<p>從這個目錄裡面，你可以用Python的<code>venv</code>模組建立一個虛擬環境：</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">python</span> -m venv .<span class="hljs-keyword">env</span><!-- HTML_TAG_END --></pre></div>
<p>你現在應該在你的空資料夾裡找到一個叫做<em>.env</em>的目錄，這個目錄就是你的虛擬環境。
You should now have a directory called <em>.env</em> in your otherwise empty folder:</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-built_in">ls</span> -a<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->.      <span class="hljs-string">..</span>    <span class="hljs-string">.env</span><!-- HTML_TAG_END --></pre></div>
<p>你可用 <code>activate</code> 和 <code>deactivate</code> 這兩個腳本來啟用或關閉你的虛擬環境：</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-comment"># Activate the virtual environment</span>
<span class="hljs-built_in">source</span> .<span class="hljs-built_in">env</span>/bin/activate

<span class="hljs-comment"># Deactivate the virtual environment</span>
<span class="hljs-built_in">source</span> .<span class="hljs-built_in">env</span>/bin/deactivate<!-- HTML_TAG_END --></pre></div>
<p>你可以執行 <code>which python</code> 指令來確認你的虛擬環境是否有被啟用：如果它指向虛擬環境的目錄，那表示你的虛擬環境已經啟用了！</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-built_in">which</span> python<!-- HTML_TAG_END --></pre></div>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START --><span class="hljs-regexp">/home/</span>&lt;user&gt;<span class="hljs-regexp">/transformers-course/</span>.env<span class="hljs-regexp">/bin/</span>python<!-- HTML_TAG_END --></pre></div>
<h3 id="">安裝相依性資源包</h3>
<p>在之前的段落中提到的使用Google Colab的情況裡，你會需要安裝相依性資源包才能繼續。你可以用 <code>pip</code> 這個資源管理工具來安裝開發版的🤗 Transformers：</p>

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	<pre><!-- HTML_TAG_START -->pip <span class="hljs-keyword">install</span> <span class="hljs-string">&quot;transformers[sentencepiece]&quot;</span><!-- HTML_TAG_END --></pre></div>
<p>你現在已經準備就緒，可以開始了！</p>


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