OnePlus 8T Oxygen OS 11.0.10.10.KB05BA
System
• Newly adapted OnePlus Buds Pro and brought new powerful features
• Newly added the screenshot feature for AOD
• Fixed the failed issue of Navigation gestures in some scenes
• Improved system stability and fixed known issues
• Updated Android security patch to 2021.08
Camera
• Optimized the portrait mode effect of the front camera
Ambient Display
• Newly added Bitmoji AOD, co-designed with Snapchat, which will liven up the ambient display with your personal Bitmoji avatar. Your avatar will update throughout the day based on your activity and things happening around you ( Path: Settings - Customization - Clock on ambient display - Bitmoji )
MD5
Full:
5e5e05c41bdec735195e026fbd89ea46
Size
Full:
2.76 GB (2966856115)
Downloads
Oxygen OS Server 1:
Full
Oxygen OS Server 2:
Full
Color OS Global Server 1:
Full
Color OS Global Server 2:
Full
Exported by MlgmXyysd Color OTA Bot@OnePlusOTA
#Oxygen#kebab#Europe#Full
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)
#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