WeST is an open-source speech recognition transcription model that achieves speech-to-text conversion in a concise format of 300 lines of code, based on a large language model (LLM). It includes a large language model, a speech encoder, and a projector, with only the projector being trainable. The development of WeST is inspired by SLAM-ASR and LLaMA 3.1, aiming to deliver efficient speech recognition capabilities through simplified code.