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Source channel @githubtrending · Post #14952 · Jul 13

#go#go_interview_questions#go_practice#golang#golang_interview_questions#golang_practice#hacktoberfest#interview#interview_practice#interview_questions#learn_to_code#learning_resources You can practice and improve your Go programming skills with an interactive web platform that offers 30 coding challenges ranging from beginner to advanced levels. It provides a live code editor with syntax highlighting, instant test results, and detailed performance analytics to help you write efficient Go code. You can track your progress on leaderboards, compare your solutions with others, and learn from detailed explanations and resources for each challenge. The platform supports easy setup via web UI, GitHub Codespaces, or command line, making it convenient to prepare for Go technical interviews and boost your coding confidence. This helps you master Go concepts and get ready for real job interviews effectively. https://github.com/RezaSi/go-interview-practice

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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