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Source channel @githubtrending · Post #15248 · Oct 25

#java#awesome#backend#computer_science#distributed_systems#high_level_design#hld#interview#interview_questions#scalability#system_design You can learn important system design concepts for free, covering topics like scalability, availability, CAP theorem, caching, databases, APIs, microservices, and distributed systems. This resource offers clear explanations, interview preparation guides, and practical design problems from easy to hard, helping you understand how to build reliable, scalable software systems. It also provides links to courses, books, newsletters, and videos to deepen your knowledge. Using these materials can improve your skills for system design interviews and real-world software architecture, making you more confident and effective in designing complex systems. https://github.com/ashishps1/awesome-system-design-resources

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@githubtrending · Post #15600 · 04/04/2026, 11:30 AM

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#python#apple_silicon#florence2#idefics#llava#llm#local_ai#mlx#molmo#paligemma#pixtral#vision_framework#vision_language_model#vision_transformer MLX-VLM lets you run, chat with, and fine-tune Vision Language Models (VLMs) plus audio/video models on your Mac using MLX—install easily with `pip install -U mlx-vlm`. Use CLI for quick text/image/audio generation (e.g., `mlx_vlm.generate --model ... --image photo.jpg`), Gradio UI for chats, Python scripts, or a FastAPI server with OpenAI-compatible endpoints supporting multi-images/videos. Features like TurboQuant cut KV cache memory by 76%, and LoRA/QLoRA fine-tuning works on consumer hardware. You benefit by experimenting with powerful multimodal AI locally—fast, memory-efficient, no cloud costs, perfect for Mac users tweaking models affordably. https://github.com/Blaizzy/mlx-vlm

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#python #apple_silicon #florence2 #idefics #llava #llm #local_ai #mlx #molmo #paligemma #pixtral #vision_framework #vision_language_model #vision_transformer