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Source channel @githubtrending · Post #14966 · Jul 16

#other#awesome#awesome_list#c#c_plus_plus#cpp#cpp_library#cppcon#libraries#list#lists#programming_tutorial#resources You can access a vast, well-organized collection of C++ libraries, frameworks, and tools that cover almost every programming need—from standard libraries, GUI, networking, and machine learning to game engines, cryptography, and more. This curated list includes popular and high-quality options like Boost, Qt, OpenCV, and many specialized libraries for tasks such as asynchronous programming, audio processing, and serialization. Using these resources can save you time, improve code quality, and help you build efficient, robust applications by leveraging tested, peer-reviewed components instead of writing everything from scratch. It’s a one-stop reference to boost your C++ development productivity and capabilities. https://github.com/fffaraz/awesome-cpp

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

#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