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Source channel @FindBlog · Post #643 · 3月1日

Flare Stack Blog ——基于 Cloudflare Workers 的现代化全栈博客 CMS ## 核心功能 • 文章管理 — 富文本编辑器,支持代码高亮、图片上传、草稿/发布流程 • 标签系统 — 灵活的文章分类 • 评论系统 — 支持嵌套回复、邮件通知、审核机制 • 友情链接 — 用户申请、管理员审核、邮件通知 • 全文搜索 — 基于 Orama 的高性能搜索 • 媒体库 — R2 对象存储,图片管理与优化 • 用户认证 — GitHub OAuth 登录,权限控制 • 数据统计 — Umami 集成,访问分析与热门文章 • AI 辅助 — Cloudflare Workers AI 集成 • 主题系统 — 可扩展的主题模板,支持完整替换所有页面和布局 • 导入导出 — 支持Markdown导入导出,保留图片以及Frontmatter Flare Stack Blog 的所有面向用户的页面与布局均通过 主题契约(Theme Contract) 与业务逻辑解耦。你可以在不修改任何路由或数据逻辑的前提下,完整替换博客的视觉表现层。 项目地址:https://github.com/du2333/flare-stack-blog #Platform#Cloudflare 频道:@FindBlog 群组:@FindBlog_Group

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GitHub Trends

@githubtrending · Post #15143 · 2025/09/14 12:00

#python#llms#mlx MLX LM is a Python tool that helps you run and fine-tune large language models (LLMs) efficiently on Apple Silicon Macs. It connects easily to thousands of models on Hugging Face, supports model quantization to save memory, and allows distributed training. You can generate text or chat with models via simple commands or Python code. It also offers features like prompt caching and memory optimization for handling long texts, making it faster and less resource-heavy. This means you can run powerful AI models locally on your Mac without needing expensive cloud services, saving cost and improving speed. https://github.com/ml-explore/mlx-lm

GitHub Trends

@githubtrending · Post #14655 · 2025/05/01 13:30

#typescript#electron#llama#llms#lora#mlx#rlhf#transformers Transformer Lab is a free, open-source tool that lets you easily work with large language models on your own computer, offering one-click downloads for popular models like Llama3 and Mistral, fine-tuning across different hardware (including Apple Silicon and GPUs), and features like chatting, training, and evaluating models through a simple interface—saving you from complex setups like CUDA or Python version issues[1][2][5]. https://github.com/transformerlab/transformerlab-app

GitHub Trends

@githubtrending · Post #15614 · 2026/04/13 11:30

#typescript#ai#cuda#mlx#qwen3_tts#qwen3_tts_ui#voice_ai#voice_clone#whisper Voicebox is a free, open-source voice synthesis studio that lets you clone voices, generate speech in 23 languages, and apply audio effects—all running privately on your computer. You can create realistic voice clones from just seconds of audio, use five different text-to-speech engines for different needs, add effects like reverb and pitch shift, and build multi-voice projects with a timeline editor. The key benefit is complete privacy: your voice data and AI models never leave your machine, unlike cloud-based alternatives. It also includes an API for building voice-powered applications and works across Mac, Windows, and Linux with GPU acceleration support. https://github.com/jamiepine/voicebox

GitHub Trends

@githubtrending · Post #14684 · 2025/05/08 12:00

#python#apple_silicon#audio_processing#mlx#multimodal#speech_recognition#speech_synthesis#speech_to_text#text_to_speech#transformers MLX-Audio is a powerful tool for converting text into speech and speech into new audio. It works well on Apple Silicon devices, like M-series chips, making it fast and efficient. You can choose from different languages and voices, and even adjust how fast the speech is. It also includes a web interface where you can see audio in 3D and play your own files. This tool is helpful for making audiobooks, interactive media, and personal projects because it's easy to use and provides high-quality audio quickly. https://github.com/Blaizzy/mlx-audio

GitHub Trends

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

#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