This repository provides the official implementation of DoLa, a decoding method that improves factuality in LLMs without requiring additional fine-tuning or external knowledge retrieval. The approach contrasts logits between early and later transformer layers to identify and suppress hallucinated tokens. The code integrates with Hugging Face Transformers and includes evaluation scripts for benchmarking factuality improvements.