Impact Highlights
Cut trainable parameters by 99% with targeted LoRA adaptation.
99Implemented DPO alignment workflow across the final transformer layers.
Merged tuned low-rank adapters for lean inference deployment.
Mission Brief
LLM Alignment and Optimization
From-scratch language model implementation and preference alignment pipeline with low-rank adaptation for efficient fine-tuning.
PyTorchLoRADPOHugging FaceTransformers
Build Notes
Implemented a 135M parameter language model from scratch using GQA, RoPE, and RMSNorm.
135MBuilt a LoRA-based DPO preference alignment pipeline over the HH dataset.
Fine-tuned Q/K/V heads and reduced trainable parameters by 99% before merging weights for inference.
99
Image Direction
Recommended Concept
A neural lattice of transformer layers with attention paths and low-rank channels highlighted as luminous conduits.
Text-to-Image Prompt
Cinematic transformer architecture scene, stacked neural blocks, electric teal and coral accents, vector field streams, futuristic research lab mood, clean minimal background, no text
Fallback asset in use: /illustrations/llm-alignment.svg