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LLM just made running 70 billion parameter AI models possible without supercomputers by loading layers from your hard drive. Its flash attention keeps memory low, letting complex models like LLAMA 3.3 70B run smoothly on MacBooks and gaming PCs. A game-changer for students and indie devs exploring AI. #llm #llama33b #aiinnovation #opensourceai #machinelearning
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LLM just made running 70 billion parameter AI models possible without supercomputers by loading layers from your hard drive. Its flash attention keeps memory low, letting complex models like LLAMA 3.3 70B run smoothly on MacBooks and gaming PCs. A game-changer for students and indie devs exploring AI. #llm #llama33b #aiinnovation #opensourceai #machinelearning
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Rest in peace, my brother. 🕊️💔 We shared so many moments, especially through the love of dance. I’ll always remember the laughs, the moves, and the memories we created together. It hurts knowing you’re gone, but your legacy will live on through every step. 🕊️❤️ Rest easy, my friend. You will never be forgotten @Delux
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Nobody ever wrote the code that lets ChatGPT write Python. Not one line of it. 🤯 Here's how a large language model actually gets built, step by step: 1️⃣ Data. Trillions of words of books, web pages, code and forums, then cleaned: duplicates removed, spam filtered, broken text stripped. One open dataset, FineWeb, is 15 trillion tokens of web text. 2️⃣ Tokens. The model never sees words.
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3 AI Projects That Can Actually Make Your GitHub Portfolio STAND OUT in 2026 🚀 If you’re learning AI Engineering, Machine Learning, Generative AI or LLMs and wondering “What projects should I build to get a job?” start here. 👇 In this video, I break down 3 job-ready AI projects that you can build and showcase on your GitHub portfolio. You’ll learn: ✅ What to build ✅ Why each project matters ✅ Which AI/ML skills it demonstrates ✅ How to structure the project ✅ What to add to your GitHub README
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