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    <title>DEV Community: Drew Jenkins</title>
    <description>The latest articles on DEV Community by Drew Jenkins (@drewworks).</description>
    <link>https://dev.to/drewworks</link>
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      <title>DEV Community: Drew Jenkins</title>
      <link>https://dev.to/drewworks</link>
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    <item>
      <title>Shipping a model behind FastAPI without the notebook</title>
      <dc:creator>Drew Jenkins</dc:creator>
      <pubDate>Tue, 27 Oct 2026 15:21:23 +0000</pubDate>
      <link>https://dev.to/drewworks/shipping-a-model-behind-fastapi-without-the-notebook-41ch</link>
      <guid>https://dev.to/drewworks/shipping-a-model-behind-fastapi-without-the-notebook-41ch</guid>
      <description>&lt;p&gt;Turned a notebook that had been "almost ready" for three weeks into an actual service this week. The model didn't change — the packaging did.&lt;/p&gt;

&lt;p&gt;What made the difference:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;One &lt;code&gt;predict.py&lt;/code&gt; with a pure function, no global state&lt;/li&gt;
&lt;li&gt;A tiny test that loads the model and runs a fixed input&lt;/li&gt;
&lt;li&gt;Docker with a pinned wheel, not a &lt;code&gt;pip install&lt;/code&gt; at boot&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;The notebook is still useful for experiments. It just isn't the deployment artifact.&lt;/p&gt;

&lt;p&gt;Next: I want to try compiling one of these small models to WebAssembly so it can run client-side. If you've done that with a PyTorch model, I'd love to hear what worked.&lt;/p&gt;

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      <category>machinelearning</category>
      <category>python</category>
      <category>api</category>
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