While Large Language Models (LLMs) demonstrate impressive capabilities in
text generation, we find that their ability has yet to be generalized to music,
humanity's creative language. We introduce ChatMusician, an open-source LLM
that integrates intrinsic musical abilities. It is based on continual
pre-training and finetuning LLaMA2 on a text-compatible music representation,
ABC notation, and the music is treated as a second language. ChatMusician can
understand and generate music with a pure text tokenizer without any external
multi-modal neural structures or tokenizers. Interestingly, endowing musical
abilities does not harm language abilities, even achieving a slightly higher
MMLU score. Our model is capable of composing well-structured, full-length
music, conditioned on texts, chords, melodies, motifs, musical forms, etc,
surpassing GPT-4 baseline. On our meticulously curated college-level music
understanding benchmark, MusicTheoryBench, ChatMusician surpasses LLaMA2 and
GPT-3.5 on zero-shot setting by a noticeable margin. Our work reveals that LLMs
can be an excellent compressor for music, but there remains significant
territory to be conquered. We release our 4B token music-language corpora
MusicPile, the collected MusicTheoryBench, code, model and demo in GitHub.

我们介绍了 ChatMusician，这是一个开源的大型语言模型，基于在 ABC 符号表示和音乐作为第二语言上进行连续预训练和微调的 LLaMA2，它能够理解和生成音乐，并能够创作结构良好、完整的音乐作品，超过了 GPT-4 基准模型。