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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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Crypto M - Crypto News

@CryptoM · Post #64625 · 04/09/2026, 11:54 AM

🚀 Independent Miner Achieves Rare Bitcoin Block Discovery An independent Bitcoin miner achieved a rare feat by successfully mining a Bitcoin block with a very low probability. According to BlockBeats, the miner used CKpool's solo mining software to mine block number 944,306, earning a total of 3.128 Bitcoin. Data from block explorer Mempool indicates that the miner received a block subsidy of 3.125 Bitcoin and transaction fees amounting to 0.003 Bitcoin. CKpool developer Con Kolivas noted on the X platform that the miner accomplished this with just 70TH of computing power. The probability of a miner of this scale discovering a block daily is approximately one in 100,000, with an average occurrence of once every 300 years. #Bitcoin#mining#CKpool#blockchain#rarefeat#blockdiscovery#cryptocurrency#soloMining#Mempool#transactionfees#ConKolivas#BTC