Run DeepSeek R1 Locally. Easiest Method

Key Concepts:

• DeepSeek R1: A powerful, free, and open-source AI model.
• Local Execution: Running AI models directly on a user's computer instead of relying on remote servers.
• LM Studio: Software used to run AI models locally.
• Model Quantization: Reducing the size and computational requirements of a model.
• Parameters: Variables that an AI model learns during training.
• Chain of Thought: The reasoning process an AI model uses to arrive at an answer.
• Privacy Implications: Concerns about data tracking and storage when using online AI services.

Running DeepSeek R1 Locally for Privacy

The video addresses the privacy concerns associated with using DeepSeek R1 on the DeepSeek website, where user data is stored on servers in China with a potentially loose privacy policy. The solution presented is to run the model locally on your own computer using LM Studio, ensuring that no data leaves your device.

Comparison of Usage Methods

• DeepSeek Website (deepseek.com):
  • Requires login.
  • Easy to use interface.
  • Privacy concerns due to data storage on Chinese servers.
  • Example prompt used: "If a plant that doubles its size every day covers a lake in 30 days, how much time will it take for two plants to cover half the lake?"
  • Demonstrates the model's "Chain of Thought" reasoning.
• Perplexity:
  • Offers 5 free queries per day.
  • Servers are located in the US.
• Groq:
  • Offers a slightly distilled model for free.
  • Insanely fast.
• LM Studio (Local Execution):
  • Provides full privacy as no data leaves the computer.
  • Requires downloading and setting up LM Studio.
  • Allows selection of different model sizes based on hardware capabilities.

Step-by-Step Guide to Running DeepSeek R1 Locally with LM Studio

1. Download LM Studio: Download the appropriate version for your operating system from the LM Studio homepage.
2. Install and Open LM Studio: Follow the installation instructions and open the application.
3. Discover Tab: Navigate to the "Discover" tab within LM Studio.
4. Search for DeepSeek: Type "deep seek" into the search bar.
5. Choose a Model: Select a DeepSeek R1 model based on your hardware capabilities. The video mentions models ranging from 8 billion parameters to 7 billion parameters. The full DeepSeek R1 with 67 billion parameters requires significant hardware.
6. Model Quantization: Choose a quantization level. The video uses "Q4_K_M" and suggests that they all feel roughly the same. LM Studio indicates if your GPU can handle the selected model with a green indicator.
7. Download the Model: Click the download button to download the selected model.
8. Select the Model: Once downloaded, go to the top of the LM Studio interface and ensure the downloaded model is selected.
9. Start Prompting: Begin entering prompts and interacting with the model. The video demonstrates that the locally run model provides the same correct answer as the online version.

Technical Details and Considerations

• Model Size and Hardware: The size of the model (number of parameters) directly impacts the hardware requirements. Larger models require more powerful GPUs and more RAM.
• Quantization: Quantization reduces the precision of the model's weights, resulting in a smaller file size and lower computational requirements. Different quantization levels (e.g., Q4_K_M) offer trade-offs between size and performance.
• GPU Support: LM Studio indicates whether your GPU can handle a specific model, making it easier to choose an appropriate model for your hardware.

Privacy Policy Concerns

The video highlights a snippet from the DeepSeek privacy policy, implying that it tracks user data in a way that raises privacy concerns. This is the primary motivation for running the model locally.

Conclusion

The video provides a practical guide to running the DeepSeek R1 AI model locally using LM Studio, addressing privacy concerns associated with using the model on the DeepSeek website. It emphasizes the ease of setup and the ability to choose model sizes based on available hardware. The key takeaway is that users can leverage the power of DeepSeek R1 while maintaining full control over their data and privacy. The video also promotes Futurepedia's AI courses for further learning.