Update README.md

README.md

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 short_description: Small, local models distilled from frontier teachers
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-![Advanced Data Intelligence](https://thelabsource.com/banners/adi_org_hero.png)
+<p align="center">
+  <img src="https://thelabsource.com/banners/adi_org_hero.png" width="720" alt="Advanced Data Intelligence">
+</p>
 
 # Advanced Data Intelligence
 
@@ -20,7 +22,9 @@ Every model here is built end-to-end on theLAB hardware — no cloud training
 
 **Links:** [Website](https://advanced-data-intelligence.com) · [theLAB](https://thelabsource.com) · [YouTube — Advanced Data Intelligence](https://www.youtube.com/@AdvancedDataIntelligence) · [YouTube — ADI Online](https://www.youtube.com/@adi_onlin3)
 
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+<p align="center">
+  <img src="https://thelabsource.com/huggingface/art/adi_divider_pulse.png" width="700" alt="">
+</p>
 
 ## Models
 
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 ollama run hf.co/AdvancedDataIntelligence/adi-qwen2.5-coder-7b-kimi2.7-code-GGUF:Q4_K_M
 ```
 
+<p align="center">
+  <img src="https://thelabsource.com/huggingface/charts/adi_lineup_chart.png" width="760" alt="ADI model lineup — size on disk">
+</p>
+
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 ## How to run
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 Then point any llama.cpp-based runtime at the downloaded file.
 
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-
-## Watch
-
-We publish short videos on AI, alignment, and how these models are built:
-
-<table>
-<tr>
-<td align="center" valign="top" width="400">
-  <a href="https://www.youtube.com/watch?v=zhPpQLPsWbs"><img src="https://img.youtube.com/vi/zhPpQLPsWbs/maxresdefault.jpg" width="380" alt="ADI AI Desktop — Alpha"></a>
-  <br><b>ADI AI Desktop — Alpha</b>
-</td>
-<td align="center" valign="top" width="240">
-  <a href="https://www.youtube.com/shorts/h9MGVaLs_sc"><img src="https://img.youtube.com/vi/h9MGVaLs_sc/hqdefault.jpg" width="215" alt="Utopia or a Cage?"></a>
-  <br><b>Utopia or a Cage? | The Benevolent Dictator</b>
-</td>
-</tr>
-</table>
-
-- **[Advanced Data Intelligence](https://www.youtube.com/@AdvancedDataIntelligence)** — the main channel.
-- **[ADI Online](https://www.youtube.com/@adi_onlin3)** — an AI philosophy series covering the alignment problem, the paperclip maximizer, the treacherous turn, the Chinese room, and more.
-
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+<p align="center">
+  <img src="https://thelabsource.com/huggingface/art/adi_divider_cat.png" width="700" alt="">
+</p>
 
 ## The approach
 
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 - **Local-first.** Every model runs fully offline on consumer hardware. No API, no data leaving the machine.
 - **Open.** Apache-2.0 where the base license allows, with full training details on each model card so the work is reproducible.
 
+<p align="center">
+  <img src="https://thelabsource.com/huggingface/charts/adi_pipeline_flow.png" width="760" alt="The ADI distillation pipeline">
+</p>
+
 ---
 
 ## Coming next
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 Models follow the pattern `adi-<base>-<size>-<teacher>-<purpose>` — so the name tells you the student base, its size, the teacher it learned from, and what it's tuned for.
 
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+<p align="center">
+  <img src="https://thelabsource.com/huggingface/art/adi_cat_hero.png" width="560" alt="ADI">
+</p>
 
 *Built at [theLAB](https://thelabsource.com) — Learning. Algorithms. Breakthroughs.*