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Akshay ๐Ÿš€
@akshay_pachaar
Simplifying LLMs, AI Agents, RAG, and Machine Learning for you! โ€ข Co-founder @dailydoseofds_โ€ข BITS Pilani โ€ข 3 Patents โ€ข ex-AI Engineer @ LightningAI
๊ฐ€์ž… July 2012
501 ํŒ”๋กœ์ž‰ ์ค‘    290K ํŒฌ
The easiest way to run your agent harnesses using local models: Whether you're using Claude Code, Codex, OpenCode, or Pi, the local setup itself isn't really the hard part. The harder problem is figuring out which local model your machine can actually handle well. You have to think about RAM, model size, quantization, context length, KV cache, speed, accuracy, and a bunch of other trade-offs before you even start. Magnitude is an open-source solution that removes all of that guesswork for you. It profiles your machine, benchmarks what it can realistically run, recommends the best models for your hardware, and then lets you connect them to your preferred agent harness. The entire setup takes just two commands. In this video, I walk through the full process from hardware profiling to running a harness on a local model. Chapters: 00:00 Intro 00:17 What Magnitude is 00:45 Setup in two commands 01:29 Why picking a local model gets confusing fast 02:11 Hardware profiling + model recommendations 02:59 Choosing your harness 03:22 Connecting a harness that's already running 04:18 Outro Get started: (don't forget to star ๐ŸŒŸ)
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