Took vLLM-SR d3-edge (0.6B), fine-tuned it with simple SFT + LoRA, and compared it against the much larger d3 (27B). With just a few thousand training examples, the 0.6B model actually outperformed the 27B model on typed decisions and nearly matched it on Banking77. I strongly believe we should be fine-tuning small, specialized decision models rather than using large general-purpose models for every task. Colab - https://colab.research.google.com/drive/1wze4PA3GBrxRLYhzzFK7czlmvAgRdA9P?usp=sharing   submitted by   /u/mshubham [link]   [comments]