DeepSeek-R1 32B on AMD Mi60: MAX QUALITY with Python & Ollama

Ready to push your local Generative AI setup to the limit?
This screencast shows you how to run the powerful **DeepSeek-R1 32B Model** on a Linux machine utilizing the **AMD Instinct Mi60 32GB HBM2 GPU**. We are using the **Python** language and the **Ollama Client** for this high-performance local inference setup.

The focus of this tutorial is simple: **BETTER QUALITY OUTPUT**.
We'll dive into the specific model settings required within the Ollama ecosystem to ensure your DeepSeek-R1 results are formatted using rich **Markdown** instead of plain text, which is crucial for superior code and documentation generation.

Whether you're migrating from a previous web UI or setting up for the first time, this is the definitive guide for high-quality, local LLM inference on AMD hardware using Python and Ollama.

### Key Timestamps
(Add your video timestamps here for chapters and better SEO)
0:00 - Introduction & Model Overview
1:30 - Linux, ROCm, and Ollama Client Prerequisites
3:45 - Running DeepSeek-R1 32B on Mi60 with Python
7:05 - The Essential Quality Setting: Markdown vs. Plain Text in Ollama
9:30 - Testing for Superior Output Quality

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### 🛠️ Resources & Previous Tutorial
* **Previous Web UI Tutorial for DeepSeek-R1:**
https://ojambo.com/web-ui-for-generative-ai-deepseek-r1-32b-model

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### 👨‍💻 Get More from Edward Ojambo
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https://ojamboshop.com/product-category/course
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https://ojambo.com/contact
* **Professional AI Installation & Migration Services (e.g., Wan 3.3 TI2V 5B):**
https://ojamboservices.com/contact

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