Master Local LLM Deployment with Docker Model Runner
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In this thrilling episode on Krish Naik's channel, we delve into the exhilarating world of running LLMs locally with Docker model runner. Picture this: developers craving the freedom to fine-tune their LLMs, conduct rigorous testing, and pit open source models against each other. The key? Docker desktop, boasting a minimum version requirement of 4.40 for the ultimate model running experience. But hold onto your seats because the real magic lies in enabling Docker model runner and host-side TCP support, unlocking a realm of possibilities right at your fingertips.
But wait, there's more! Strap in as we navigate through a command prompt journey to verify and activate the model runner, ensuring seamless operation. With a quick check on the status using "docker model status," we're all set to explore a treasure trove of commands like inspect, list, pull, push, and run. And that's just the tip of the iceberg. The adrenaline rush continues as we venture into Docker Hub, uncovering a myriad of LLM models ripe for the picking. From llama 3.2 for chat assistance to text extraction, the options are as vast as the open road ahead.
Rev up your engines as we hit the gas on pulling a model with the command "docker model pull AI/small_lnm2" and kicking it into high gear with "docker model run AI/small_lnm2." Experience the sheer thrill of engaging in dynamic conversations and extracting information with just a few keystrokes. And when it's time to bid adieu, a simple "/bye" brings the chat session to a close. But the excitement doesn't stop there. Buckle up as we take a detour into real-time interactions with the model, where facts and questions are met with lightning-fast responses, all within the confines of local operation. And the cherry on top? Seamless compatibility with the OpenAI library, bridging the gap between cutting-edge technology and user-friendly accessibility.
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