paper implementations
PyTorch implementations of research papers, aimed at deepening my understanding of the underlying concepts.
PyTorch implementations of research papers, aimed at deepening my understanding of the underlying concepts.
Implementation of four self-supervised learning (SSL) algorithms; SimCLR, MoCo-v2, BYOL, and DINO on the CIFAR-10 dataset using a ResNet-18 backbone. All scripts are designed to run on Google Colab Free Tier (single GPU, ~12 GB RAM) with CIFAR-10.
Abstract PyTorch pipeline that uses a hypernetwork to generate task-specific LoRA adapters for Meta’s Segment Anything Model from natural language prompts, targeted segmentation on COCO instances and benchmarked mIoU via pycocotools. Links You can find the repo here.