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103 changes: 52 additions & 51 deletions api-reference/model/index.html
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2 changes: 1 addition & 1 deletion extract/dataclass/index.html
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Expand Up @@ -1770,7 +1770,7 @@ <h2 id="field-annotations">Field annotations<a class="headerlink" href="#field-a
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<p>In this manner, the model can be informed of what is wanted for each specific field.</p>
<p>Check the <a href="../../examples/extract_dataclass/">Extract dataclass example</a>.</p>
<p>Check the <a href="../../examples/extract_dataclass/">Extract dataclass example</a> to see this in action.</p>



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Expand Up @@ -1772,6 +1772,7 @@ <h2 id="enum-classes">Enum classes<a class="headerlink" href="#enum-classes" tit
</span><span id="__span-6-3"><a id="__codelineno-6-3" name="__codelineno-6-3" href="#__codelineno-6-3"></a> <span class="n">YELLOW</span> <span class="o">=</span> <span class="s1">&#39;slow down&#39;</span>
</span><span id="__span-6-4"><a id="__codelineno-6-4" name="__codelineno-6-4" href="#__codelineno-6-4"></a> <span class="n">GREEN</span> <span class="o">=</span> <span class="s1">&#39;go&#39;</span>
</span></code></pre></div>
<p>See the <a href="../../examples/tag/">Tag classification example</a> to see how Enum is used to tag support queries.</p>
<h2 id="classify">Classify<a class="headerlink" href="#classify" title="Permanent link">#</a></h2>
<p>You can also use the <a href="../../api-reference/model/#sibila.LlamaCppModel.classify">classify()</a> method to extract enumerations, which accepts the enum types we've seen above. It calls extract() internally and its only justification is to make things more readable:</p>
<div class="admonition example">
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Expand Up @@ -1768,7 +1768,7 @@ <h2 id="field-annotations">Field annotations<a class="headerlink" href="#field-a
</div>
</div>
<p>In this manner, the model can be informed of what is wanted for each specific field.</p>
<p>Check the <a href="../../examples/extract/">Extract Pydantic example</a>.</p>
<p>Check the <a href="../../examples/extract/">Extract Pydantic example</a> to see this kind of extraction.</p>



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Expand Up @@ -1648,7 +1648,7 @@ <h1>Models factory</h1>
<ul>
<li>A remote model name, like "gpt-4": "openai:gpt-4"</li>
<li>A local model name, like "openchat": "llamacpp:openchat"</li>
<li>The actual filename of a model in the "models" folder: "llamacpp:openchat-3.5-1210.Q4_K_M.gguf"</li>
<li>The actual filename of a model in the "models" folder: "llamacpp:openchat-3.5-1210.Q4_K_M.gguf" - this is the form we use in the examples, but of course using "openchat" instead of the filename would be better...</li>
</ul>
<p>Although you can use filenames as model names, it's generally a better idea, for continued use, to create an entry in the "models.json" file - this allows future model replacement to be much easier.</p>
<p>See <a href="../models_json/">Managing models</a> to learn how to register these model names.</p>
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Expand Up @@ -1716,7 +1716,7 @@ <h1>What can you do with Sibila?</h1>
<p>This not only simplifies handling the model responses but can also open new possibilities: you can now deal with the model in a structured way.</p>
<h2 id="extract-pydantic-dataclasses-or-simple-types">Extract Pydantic, dataclasses or simple types<a class="headerlink" href="#extract-pydantic-dataclasses-or-simple-types" title="Permanent link">#</a></h2>
<p>To specify the structured output that you want from the model, you can use Pydantic's BaseModel derived classes, or the lightweight Python dataclasses, if you don't need the whole Pydantic.</p>
<p>With Sibila, you can also use simple types like bool, int, str, enumerations or lists.
<p>With Sibila, you can also use simple data types like bool, int, str, enumerations or lists.
For example, need to classify something? </p>
<div class="admonition example">
<p class="admonition-title">Example</p>
Expand All @@ -1733,6 +1733,7 @@ <h2 id="extract-pydantic-dataclasses-or-simple-types">Extract Pydantic, dataclas
</span></code></pre></div>
</div>
</div>
<p>How does it work? Extraction to the given data types is guaranteed by automatic JSON Schema grammars in local models, or by the Tools functionality of OpenAI API remote models.</p>
<h2 id="from-your-models-or-openais">From your models or OpenAI's<a class="headerlink" href="#from-your-models-or-openais" title="Permanent link">#</a></h2>
<p>Small downloadable 7B parameter models are getting better every month and they have reached a level where they are competent enough for most common data extraction or summarization tasks.</p>
<p>With 8Gb or more of RAM or GPU memory, you can get good structured output from models like OpenChat, Zephyr, Mistral 7B, or any other GGUF file.</p>
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