A from-scratch implementation of a scaled-down GPT-2 model in PyTorch, trained on the Snappfood dataset for sentiment-controlled Persian text generation.

LLM pipeline: data→tokenizer→attention→GPT train/eval→instruction FT→sampling. Reproducible, clean configs, RTX-4060 defaults, ready for AMP/LoRA/DDP.

VEHANT Causal Temporal Action Detection System: State-of-the-art deep learning for real-time fight/collapse detection in videos. Features causal attention, motion tokenization, MediaPipe skeletons, uncertainty quantification, and multi-task learning (class + bbox + temporal). 95% accuracy, ONNX/Docker-ready, 25ms GPU inference. 🚀