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Source channel @githubtrending · Post #14880 · Jun 28

#go#github_actions#kubernetes#operator Actions Runner Controller (ARC) is a tool that helps you automatically manage and scale self-hosted GitHub Actions runners using Kubernetes. It creates runner scale sets that grow or shrink based on how many workflows you are running, making your CI/CD process more efficient and cost-effective. ARC uses containers for runners, so new instances can start or stop quickly and cleanly. You can install ARC easily with Helm on Kubernetes and customize runners with features like custom images, volumes, and scripts. This automation saves you time and resources by matching runner capacity to your actual workload needs[1][2][3]. https://github.com/actions/actions-runner-controller

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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