Polish lab link buttons
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@@ -60,7 +60,7 @@ The project’s original goal was to make LLaMA models accessible on systems wit
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[HuggingFace](https://huggingface.com) is the “GitHub” for LLMs, datasets, and more. The following steps walk you through locating Meta’s **LLaMA‑3.2‑1B** model card and its files.
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1. **Open the LLaMA‑3.2‑1B page**
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<https://huggingface.co/meta-llama/Llama-3.2-1B>
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<a class="lab-open-pill" href="https://huggingface.co/meta-llama/Llama-3.2-1B" target="_blank" rel="noreferrer">LLaMA-3.2-1B on Hugging Face</a>
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<br>
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2. **Read the model card** – note the description, license, tags (e.g., _Text Generation_, _SafeTensors_, _PyTorch_), and links to fine‑tunes/quantizations.
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<br>
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@@ -104,7 +104,7 @@ For this lab we will work with **WhiteRabbitNeo‑V3‑7B**, a cybersecurity‑o
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### 1. Locate & download the model
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1. Go to <https://huggingface.co/WhiteRabbitNeo/WhiteRabbitNeo-V3-7B>.
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1. Go to <a class="lab-open-pill" href="https://huggingface.co/WhiteRabbitNeo/WhiteRabbitNeo-V3-7B" target="_blank" rel="noreferrer">WhiteRabbitNeo-V3-7B on Hugging Face</a>.
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2. Points of Interest on this modelcard:
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1. This model appears to be a fine tune of **Qwen2.5-Coder-7B**
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2. This model is openly licensed, and does have any requirements to download and use for our purposes.
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@@ -237,7 +237,7 @@ Ollama is a lightweight framework that hides the low‑level steps required by L
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Lets start by downloading Meta's llama3.2-3b, the "big" brother to the small model we've continuously worked with so far. The Ollama project and community have made this exceptionally easy for us to accomplish.
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1. **Open the Ollama registry** – visit <https://ollama.com> in your browser.
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1. **Open the Ollama registry** – visit <a class="lab-open-pill" href="https://ollama.com" target="_blank" rel="noreferrer">Ollama registry</a> in your browser.
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2. **Search for the model**
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<figure style="text-align: center;">
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@@ -95,7 +95,7 @@ Locate, pull, and run **Qwen3.5 4B** using the **Open WebUI**. By defualt, Ope
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- Click the **copy‑to‑clipboard** icon next to the tag (or highlight the text and press **Ctrl +C**).
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6. **Open the Open WebUI interface**
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- In a new browser tab, navigate to the URL where your Open WebUI instance is running (e.g., `http://localhost:8080`).
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- In a new browser tab, navigate to {{service-url:open-webui}}.
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7. **Pull the model through the UI**
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- In the **“Select a model”** dropdown, paste the copied tag into the text field.
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@@ -33,7 +33,7 @@ Before we install any harness, we need a key that lets the harness call the same
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### Execute: Sign in to Open WebUI
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1. Navigate to `{{service-url:open-webui}}`.
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1. Navigate to {{service-url:open-webui}}.
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2. Sign in with the same account you used in Lab 4, or the credentials supplied by your instructor.
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3. Confirm that you can reach the normal chat screen before continuing.
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