TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15033 · Aug 6

#shell#buildroot_external_tree#firmware#ingenic#ip_camera#ipc#ipcamera Thingino is free, open-source firmware designed specifically for IP cameras using Ingenic SoC chips. It customizes the software to fit each supported camera model, making the camera easier to use and more efficient. You can build the firmware yourself using the provided instructions and tools, and there is a helpful web interface to control camera features like pan, tilt, night mode, and streaming. This gives you more control and flexibility over your camera without relying on proprietary software. It supports many camera models, and the community offers resources like a wiki, chat groups, and development guides to help you get started and customize your device. This benefits you by providing a customizable, transparent, and community-supported alternative to closed camera firmware. https://github.com/themactep/thingino-firmware

Results

2 similar posts found

Search: #llava

当前筛选 #llava清除筛选
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)

Hashtags

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