
Building Real-World LLM Products with Fine-Tuning and More with Hamel Husain - #694
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Unlocking Fine-Tuning with LoRa
This chapter explores LoRa (low-rank adaptation) as an efficient method for fine-tuning machine learning models by using small adapters instead of modifying all model weights. It highlights the advantages of LoRa, including smoother loss surfaces, customizable adapters, and reviews various inference frameworks like Nvidia Triton and VLM.
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