<ul><li>Running LLMs locally using tools like Ollama, LM Studio, and HuggingFace has become more accessible on consumer-grade hardware.</li><li>Benefits of running LLMs locally include privacy, cost savings, customization, and offline access, making it ideal for developers, researchers, and businesses.</li><li>Options for running LLMs locally include Ollama for simple setup, LM Studio for GUI interface, and HuggingFace Transformers for flexibility for Python developers.</li><li>Hardware requirements, quantization tips, fine-tuning guide with QLoRA, and performance benchmarks for models like Mistral, LLaMA 3, and Gemma are covered in the guide.</li></ul>

Running LLMs Locally: Using Ollama, LM Studio, and HuggingFace on a Budget

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