#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
#Elezioni#Romania#Presidenziali
Risultati definitivi:
Affluenza: 53,21% (+0,65 rispetto al 2024)
George #Simion (#AUR|ECR): 40,96%
Nicușor #Dan (supp. #USR-#DREPT-#PMP-#FD-#REPER-#PRA-#Verzii|EPP|RE|G/EFA): 20,99%
Crin #Antonescu (supp. #ARo|S&D|EPP): 20,07%
Victor #Ponta: 13,04%
Elena #Lasconi (#USR|RE): 2,68%
Lavinia #Șandru (#PUSL|Centro umanista populista): 0,64%
Daniel #Funeriu: 0,43%
Cristian #Terheș (#PNCR|ECR): 0,39%
Sebastian #Popescu (#PNR|Populisti): 0,28%
John Ion #Banu: 0,23%
Silviu #Predoiu (#PLAN|Centro): 0,18%
Necessario un secondo turno tra Simion e Dan.
In foto, la mappa del voto.
@OsservatorioEsteri