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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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Venture Village Wall 🦄

@venturevillagewall · Post #3607 · 12/20/2024, 07:00 PM

o3 & o3-mini Break Benchmark Records The performance of o3 and o3-mini showcases state-of-the-art (SOTA) results across various benchmarks. Key insights include: - Frontier Math scores increased from 2% to 25%. - SWE-Bench achieved 71.7%, a significant leap for a startup that recently raised $200 million with 13.86% earlier this year. - ELO on Codeforces reached 2727, held by only 150 individuals globally. - ARC-AGI model scored 87.5%, breaking a five-year deadlock. - Noteworthy progress on GPQA and AIME benchmarks. Access to o3-mini is currently available to security researchers, while general public access is set for late January. Full access to o3 will follow later. #AI#SOTA#Benchmarks#o3#o3-mini #FrontierMath#SWE-Bench #Codeforces#ELO#ARC-AGI #GPQA#AIME#Funding#Progress#Research#Technology#Innovation

Venture Village Wall 🦄

@venturevillagewall · Post #3606 · 12/20/2024, 06:41 PM

O3 and O3-Mini Benchmark Breakthroughs The O3 and O3-Mini models showcase state-of-the-art (SOTA) performance with significant leaps in various benchmarks. Results on Frontier Math have jumped from 2% to 25%. The SWE-Bench model achieved a score of 71.7%, while a startup has raised $200 million following results of 13.86%. ELO on Codeforces reached 2727, surpassing most peers globally. Notably, the ARC-AGI model scored 87.5%, breaking a five-year benchmark. Access for security researchers to O3-Mini starts today, with general access available in late January. #O3#O3Mini#SOTA#Benchmarks#AI#ML#Funding#Codeforces#ARC-AGI #FrontierMath#SWE-Bench #ELO#GPQA#AIME#SecurityResearch#TechUpdates#Innovations#Startups#Performance#AIModels