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    <title>DEV Community: akitoow</title>
    <description>The latest articles on DEV Community by akitoow (@akitoow).</description>
    <link>https://dev.to/akitoow</link>
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      <title>Stop Getting "Slop" from Local LLMs: A Prompt &amp; Inference Framework</title>
      <dc:creator>akitoow</dc:creator>
      <pubDate>Sat, 24 Oct 2026 01:07:24 +0000</pubDate>
      <link>https://dev.to/akitoow/stop-getting-slop-from-local-llms-a-prompt-inference-framework-35dp</link>
      <guid>https://dev.to/akitoow/stop-getting-slop-from-local-llms-a-prompt-inference-framework-35dp</guid>
      <description>&lt;p&gt;Hey everyone, I've spent the last few weeks frustrated with local models (mainly 8B/7B ones like Llama-3 and Mistral) outputting markdown filler, conversational slop, or getting stuck in infinite loops when I just want raw, production-ready code. &lt;/p&gt;

&lt;p&gt;I did some extensive testing with Ollama and LM Studio and found a few sweet spots that force the models to behave like strict deterministic functions rather than conversational chatbots. Wanted to share what’s working for me.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;1. The Context-Task-Constraint (CTC) Framework&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Stop giving local models multi-step conversational prompts. They lose attention. Break it down strictly:&lt;/p&gt;

&lt;p&gt;[CONTEXT] Stack: Python 3.11, FastAPI. &lt;/p&gt;

&lt;p&gt;[TASK] Write a CRUD router.&lt;/p&gt;

&lt;p&gt;[CONSTRAINT] No markdown, no explanations, only valid code.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;2. Hyperparameter Sweet Spots (Crucial for Code)&lt;/strong&gt;&lt;br&gt;
Stop using default chat settings. If you want logic:&lt;/p&gt;

&lt;p&gt;Temperature: 0.15 (Keeps syntax logical)&lt;/p&gt;

&lt;p&gt;Top_P: 0.9 &lt;/p&gt;

&lt;p&gt;Repetition Penalty: 1.15 - 1.18 (This is the magic number to stop 8B models from repeating the same function infinitely).&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;3. XML for Context Injection&lt;/strong&gt;&lt;br&gt;
If you are pasting server logs or reference code, wrap them in  and  XML tags. Local models respect XML boundaries way better than quotes or markdown ticks.&lt;/p&gt;

&lt;p&gt;Hope this helps someone save a few hours of debugging inference settings!&lt;/p&gt;

&lt;p&gt;_P.S. I compiled all my anti-slop system prompts, zero-shot matrices, and ready-to-use Modelfiles into a clean, developer-friendly Markdown (.md) cheat sheet that you can drop directly into Obsidian or VS Code. If you want to grab the full file and support my late-night testing, I put it up here for a coffee ($5): &lt;a href="https://devtoolkit.sell.app/product/product-1792791949" rel="noopener noreferrer"&gt;https://devtoolkit.sell.app/product/product-1792791949&lt;/a&gt;&lt;br&gt;
_&lt;/p&gt;

&lt;p&gt;here for a coffee ($5): &lt;a href="https://devtoolkit.sell.app/product/product-1792791949" rel="noopener noreferrer"&gt;DevToolkit: Local LLM Mastery&lt;/a&gt;*&lt;/p&gt;

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      <category>ai</category>
      <category>python</category>
      <category>machinelearning</category>
      <category>productivity</category>
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      <title>---
title: Stop Getting "Slop" from Local LLMs: A Prompt &amp; Inference Framework
published: true
tags: ai, python, machinelearning, productivity
---

Hey everyone, I've spent the last few weeks frustrated with local models (mainly 8B/7B ones like Llama-3 and</title>
      <dc:creator>akitoow</dc:creator>
      <pubDate>Sat, 24 Oct 2026 01:00:09 +0000</pubDate>
      <link>https://dev.to/akitoow/-title-stop-getting-slop-from-local-llms-a-prompt-inference-framework-published-true-1gdg</link>
      <guid>https://dev.to/akitoow/-title-stop-getting-slop-from-local-llms-a-prompt-inference-framework-published-true-1gdg</guid>
      <description></description>
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