{"repo":"spandan11106/BDH-Explainer","free":true,"listed":false,"github":"https://github.com/spandan11106/BDH-Explainer","clone":"git clone https://github.com/spandan11106/BDH-Explainer.git","description":"A comprehensive three-part project that implements, visualizes, and teaches the Baby Dragon Hatchling (BDH) neural architecture—a biologically inspired, linear-scaling alternative to standard Transformer attention.","language":"Python","stars":10,"topics":["deep-learning","machine-learning","medical-ai","nextjs","transformer"],"license":"MIT","category":"machine-learning","readme_excerpt":"BDH-Explainer Table of Contents - What We Built - What Insight It Reveals About BDH - Project Structure - How to Access the Hosted Demo - How to Run Locally - Video Demo and Images - Team Members and Contributions - Limitations and Future Scope - License What We Built BDH-Explainer is a three-part project that implements, visualizes, and teaches the Baby Dragon Hatchling (BDH) architecture — a biologically inspired alternative to standard Transformer attention. The BDH-implementation component applies BDH linear attention to a medical diffusion model (Bdh-DiT) that predicts longitudinal brain tumor progression from MRI slices, using treatment-aware conditioning and joint image-segmentation generation. The BDH-visualizer is an interactive Next.js + Three.js web application backed by a FastAPI server that lets users explore BDH internals — neuron activations, token embeddings with RoPE transformations, and next-token prediction distributions — through 3D visualizations in real time. The Understanding BDH component is a six-part YouTube tutorial series with accompanying slides that walks through the original research paper section by section. --- What Insight It Reveals About BDH Integrating BDH into a medical diffusion pipeline surfaces a clear gap between architectural promise and practical inference behavior — and shows exactly what it takes to close it: - Sparse linear attention is the real strength. The BDH blocks reduce memory growth from O(N^2) to O(N) relative to standar","default_branch":null,"files":null,"tree":[],"storefront":"/r/spandan11106","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/spandan11106/BDH-Explainer/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}