Dream is a large diffusion language model (dLLM) with 7 billion parameters. Unlike traditional autoregressive LLMs, it generates text using a diffusion process. The project includes training code, evaluation code, and related variants for code generation (Dream-Coder) and infilling (DreamOn). It builds on the Huggingface transformers library and supports fine-tuning on custom datasets.