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Source channel @githubtrending · Post #15237 · Oct 19

#python#text_to_speech#tts#voice_clone#zero_shot_tts OpenVoice is a free, open-source tool that lets you clone any voice using just a short audio sample, then generate speech in that voice across many languages and accents[1][5][8]. You can fine-tune how the voice sounds—adjusting emotion, accent, rhythm, pauses, and intonation—to match your needs[1][3][5]. A major benefit is “zero-shot” cloning: you can make the cloned voice speak languages it was never trained on, which is rare in voice AI[1][3][4]. The latest version, OpenVoice V2, offers even better sound quality, supports six major languages natively, and is free for both personal and commercial use[1]. This makes it easy and affordable for anyone to create realistic, customizable voice content without needing technical expertise or expensive software. https://github.com/myshell-ai/OpenVoice

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Илья AGI TV 🤖

@ilia_plasma · Post #148 · 10/08/2023, 12:16 PM

Пока весь мир ждет доступа к новой модели со зрением GPT-4V(ision), опенсорс команда (пара азитов со степенью PhD из американских вузов) уже выпустили свой аналог и бесплатную версию #LLaVA (Large Language and Vision Assistant), которая выдает результат (не) хуже GPT4V и может работать локально. Вот такая скорость развития и конкуренции в этом новом #AI рынке. 🧠LLava - вебсайт 📄WhitePaper 🧬Github code 🔋Demo для потестить на своих дикпиках 🦒Colab (для запуска у себя на серваке)

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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