Small, open-source LLMs can deliver GPT-4 level performance through the power of fine-tuning at a fraction of the cost-you can visit LoRA Land (predibase.com/..., our collection of 25 fine-tuned Mistral models to see this in action.
But what does it take to successfully fine-tune models fast and efficiently?
We’ve taken our experiences fine-tuning 1,000s of LLMs to build a state-of-the-art fine-tuning and serving stack and now we’re sharing those best practices with you.
In this technical deep dive and interactive discussion you'll learn:
• About the latest fine-tuning optimization techniques like Flash attention 2, CUDA kernels, fused optimizers, batch size tuning, and more.
• How each of these optimizations perform from a metrics perspective
• How we implemented these techniques in Predibase
• How to get started fine-tuning your own LLMs
Resources to help get you started:
• $25 in free Predibase credits: pbase.ai/getst...
• Download the slides: pbase.ai/3WAaYQL
Негізгі бет How we accelerated LLM fine-tuning by 15x in 15 days
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