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Source channel @olddriverGDstudy · Post #10 · Mar 17

#语录 请大家做个素质狼友: 1 人和人需要的是相互尊重的,希望我们群的狼友能尊重老师。在相互尊重的情况下我相信大家会得到更好的体验。 2 请大家预约老师后如有变化应该尽快,提前的告知老师,因为老师每天的课时都是有限的。如果不提前告知也很可能再也约不到这位老师或者进入妹子们的黑名单。 3 请大家遵守行规(按照行规S了但是可以待够时间,享受下老师的服务和老师聊聊天。就算时间到了没S也算是课时结束了,如果第一次结束了又做第二次那么不管S没有都应该按PP付费。),一般情况下P是60分钟 PP是90分钟 时间没到老师赶你走是老师的问题,但是超时就是狼友的问题,关于超时最好和老师协商一下,因为老师如果后面有学生,那么超时就会影响到后面的学生,很可能会给老师带来不必要的麻烦。如果想约PP的学生最好在预约的时候就给老师讲清楚。 4 关于等候的时间,有些时候有很多不可控因素比如学生迟到,学生学习时间长等因素,希望大家在等候的时候能稍微耐心点,个人感觉等候时间在20-30分钟还是可接受的。 5 希望我们群的兄弟都能做个素质狼友,当然我们也会对群里的各位老师有所要求,大家对老师有什么不满意的都可以在群里直接投诉,或者找管理员投诉。

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GitHub Trends

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

#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 · 05/01/2025, 01:30 PM

#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 · 04/13/2026, 11:30 AM

#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 · 05/08/2025, 12:00 PM

#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 · 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