We've taken on the exciting challenge of implementing the cutting-edge strategies presented in "ZEPHYR: Direct Distillation of LM Alignment". This paper's approach is not just theoretical—it's a blueprint for a significant leap in language model training. By adopting ZEPHYR's distilled direct preference optimization (dDPO), we've embarked on a code journey that brings these innovations from concept to reality. …
Model fine-tuning and quantization play pivotal roles in creating efficient and robust machine learning solutions. This blog post explores the fine-tuning process of the Zephyr 7B GPT-Q model using 4-bit quantization to boost its performance for custom data inference tasks. …