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Source channel @githubtrending · Post #15600 · Apr 4

#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

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Libertà è ragione

@libertaeragione · Post #4455 · 03/11/2026, 11:11 AM

#Elezioni#Nepal Risultati definitivi: Affluenza: 58,07% (-3,34 rispetto al 2022, proporzionale) #RSP|Centro-sinistra: 182 seggi (+162 rispetto al 2022) #NC|Centro-sinistra: 38 (-51) #CPNUML|Sinistra: 25 (-53) #NCP|Sinistra radicale: 17 (-28) #SSP|Populisti per la democrazia di base: 7 (+7) #RPP|Destra monarchica indù: 5 (-9) Indipendenti: 1 (-2) #PSPN|Centro-sinistra federalista: 0 (-12) #JP|Sinistra del Terai: 0 (-12) #NWPP|Juche: 0 (-1) #RJ|Estrema sinistra anti-federalista: 0 (-1) Totale seggi: 275 Maggioranza: 138 In foto, la mappa del voto. @OsservatorioEsteri