<ul><li>Running AI models locally is becoming more popular to avoid cloud-based limitations and privacy concerns.</li><li>Ollama + LLMs like DeepSeek-R1 offer a game-changing solution for AI development without cloud hassles.</li><li>Installation of Ollama is straightforward, enabling local AI model deployment in minutes.</li><li>Hardware requirements for running DeepSeek-R1 locally include minimum 8GB RAM and a modern CPU.</li><li>Ollama simplifies model management, allowing easy selection and deployment of different model sizes.</li><li>Users can interact with AI models through chat sessions, file text processing, and parameter adjustments for varied outputs.</li><li>Integrating Ollama with a REST API for real-world applications is achievable with simple commands.</li><li>The use of Apidog for API testing with local LLMs like DeepSeek-R1 enhances debugging capabilities for AI responses.</li><li>Real-world applications of DeepSeek-R1 include content generation, information extraction, and code generation with impressive results.</li><li>Troubleshooting tips are provided for common issues like out-of-memory errors and API connection problems.</li></ul>

Ollama Cheatsheet: Running LLMs Locally with Ollama

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