TGTGInsighttelegram intelligenceLIVE / telegram public index
← GZ学习频道

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @olddriverGDstudy · Post #58 · Mar 27

#风哥避孕套如何选择课堂笔记 都说了多少遍了,别TMD买冈本,冈本TMD容易破 油少,一样的价钱不会买旁边的相模啊,玻尿酸套子也有缺点虽然润但是时间久了干的快,沐浴乳我不挑但是有一个沐浴乳我拒绝 ,力士的薰衣草真的不好闻,冈本最大的问题就是他油放的少拿出来就干,要润就玻尿酸 然后赤尾有小储精囊跟无储精囊套 要感觉我都是用浮点的,浮点套女的感觉来得快,有些人就马眼有感觉的这么办 不过无储精囊适合做多了跟射精量不大的用要不然会破的,超市就买杜蕾斯 杰士邦 相模,淘宝你看中啥买啥,然后小科普 0.01都是聚氨酯套 其他的都是乳交套,名流的玻尿酸套还是不错的,套子我是不追求的薄的,套子主要是为了安全还有就是润,很多套子很润但是油少玻尿酸少了也不行,像玻尿酸套子虽然很润但是也干的快,捷古斯也算日本大牌了,蝴蝶套一个形容 牌子叫捷古斯 因为包装上印着蝴蝶,买啥套子真的是最啥太大追求就用JS的套子 干了就跟JS说换个套子 #知识#避孕套

Results

5 similar posts found

Search: #mlx

当前筛选 #mlx清除筛选
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