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Lab 5 Moved to Unsloth

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@@ -112,6 +112,15 @@ Locate, pull, and run **Qwen3.5 4B** using the **Open WebUI**. By defualt, Op
<figcaption>Successful inference – the model returns a coherent answer.</figcaption>
</figure>
9. **Download Gemma3n e2B**
* While we're downloading models, let us download one more. You can either repeat the process from the previous steps to find and download **Gemma3n e2B**, or just use the following model tag to download the model via the Open WebUI search bar:
```bash
ollama pull gemma3n:e2b
```
Google has designed gemma 3n models designed for efficient execution on resource constrained devices such as laptops, tablets, phones, or Nvidia 2080 Super GPUs.
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@@ -203,7 +212,11 @@ Feel free to continue to explore with other topics or images. Note how each tim
### Explore: Prompt Engineering & System Prompting
<div class="lab-callout lab-callout--warning">
<strong>Warning:</strong> As you explore chat via Open WebUI, ensure you turn <code>think (Ollama)</code> to OFF. Qwen3.5 4b is likely to enter an infinite thinking loop for these tasks otherwise, which will require a VM reboot.
<strong>Warning:</strong> As you explore chat via Open WebUI, ensure you turn <code>think (Ollama)</code> to OFF. <strong>Qwen3.5 4B</strong> is likely to enter an infinite thinking loop for these tasks otherwise, which will require a VM reboot.
<br><br>
Alternatively, choose to perform these steps with **Gemma3n e2B**, which can handle tight environments more gracefully.
</div>
Next, lets review different ways we can coax a model to perform better, without having to perform fine tuning or parameter customization. We can do this by "priming" the model with our first prompt in a number of ways: