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<h1>Textual Inversions</h1>
<h2 id="using-textual-inversion-files">Using Textual Inversion Files<a class="headerlink" href="#using-textual-inversion-files" title="Permanent link">#</a></h2>
<p>Textual inversion (TI) files are small models that customize the output of
Stable Diffusion image generation. They can augment SD with specialized subjects
and artistic styles. They are also known as "embeds" in the machine learning
world.</p>
<p>Each TI file introduces one or more vocabulary terms to the SD model. These are
known in InvokeAI as "triggers." Triggers are denoted using angle brackets
as in "&lt;trigger-phrase&gt;". The two most common type of
TI files that you'll encounter are <code>.pt</code> and <code>.bin</code> files, which are produced by
different TI training packages. InvokeAI supports both formats, but its
<a href="../TRAINING/">built-in TI training system</a> produces <code>.pt</code>.</p>
<p><a href="https://huggingface.co/sd-concepts-library">Hugging Face</a> has
amassed a large library of &gt;800 community-contributed TI files covering a
broad range of subjects and styles. You can also install your own or others' TI files
by placing them in the designated directory for the compatible model type</p>
<h3 id="an-example">An Example<a class="headerlink" href="#an-example" title="Permanent link">#</a></h3>
<p>Here are a few examples to illustrate how it works. All these images
were generated using the legacy command-line client and the Stable
Diffusion 1.5 model:</p>
<table>
<thead>
<tr>
<th style="text-align: center;">Japanese gardener</th>
<th style="text-align: center;">Japanese gardener &lt;ghibli-face&gt;</th>
<th style="text-align: center;">Japanese gardener &lt;hoi4-leaders&gt;</th>
<th style="text-align: center;">Japanese gardener &lt;cartoona-animals&gt;</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align: center;"><img alt="" src="../../assets/concepts/image1.png" /></td>
<td style="text-align: center;"><img alt="" src="../../assets/concepts/image2.png" /></td>
<td style="text-align: center;"><img alt="" src="../../assets/concepts/image3.png" /></td>
<td style="text-align: center;"><img alt="" src="../../assets/concepts/image4.png" /></td>
</tr>
</tbody>
</table>
<p>You can also combine styles and concepts:</p>
<figure>
<table>
<thead>
<tr>
<th style="text-align: center;">A portrait of &lt;alf&gt; in &lt;cartoona-animal&gt; style</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align: center;"><img alt="" src="../../assets/concepts/image5.png" /></td>
</tr>
</tbody>
</table>
</figure>
<h2 id="installing-your-own-ti-files">Installing your Own TI Files<a class="headerlink" href="#installing-your-own-ti-files" title="Permanent link">#</a></h2>
<p>You may install any number of <code>.pt</code> and <code>.bin</code> files simply by copying them into
the <code>embedding</code> directory of the corresponding InvokeAI models directory (usually <code>invokeai</code>
in your home directory). For example, you can simply move a Stable Diffusion 1.5 embedding file to
the <code>sd-1/embedding</code> folder. Be careful not to overwrite one file with another.
For example, TI files generated by the Hugging Face toolkit share the named
<code>learned_embedding.bin</code>. You can rename these, or use subdirectories to keep them distinct.</p>
<p>At startup time, InvokeAI will scan the various <code>embedding</code> directories and load any TI
files it finds there for compatible models. At startup you will see a message similar to this one:</p>
<p><div class="highlight"><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a>&gt;&gt;<span class="w"> </span>Current<span class="w"> </span>embedding<span class="w"> </span>manager<span class="w"> </span>terms:<span class="w"> </span>&lt;HOI4-Leader&gt;,<span class="w"> </span>&lt;princess-knight&gt;
</code></pre></div>
To use these when generating, simply type the <code>&lt;</code> key in your prompt to open the Textual Inversion WebUI and
select the embedding you'd like to use. This UI has type-ahead support, so you can easily find supported embeddings.</p>
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