**MuScriptor** is a **multi-instrument music transcription model** — audio in, MIDI out — built by **Kyutai** and **Mirelo**, and it has picked up **1,059 stars and 134 forks** since the repository opened on **2 July 2026**. The project calls itself "the most accurate open-source transcription model," a claim it backs with an accompanying paper, *MuScriptor: An Open Model for Multi-Instrument Music Transcription* ([arXiv:2607.08168](https://arxiv.org/abs/2607.08168)), authored by Simon Rouard, Michael Krause, Axel Roebel, Carl-Johann Simon-Gabriel, and **Alexandre Défossez** — the same researcher behind Demucs and Moshi. The architecture is deliberately plain: a **transformer decoder only**, published in three sizes. **`small` is 103M parameters** (14 layers, width 768), **`medium` is 307M** (24 layers, width 1024) and is the default speed/accuracy trade-off, and **`large` is 1.4B** (48 layers, width 1536). The team's guidance is that `small` is the realistic pick on a CPU-only machine while `large` really wants a GPU. On Apple Silicon the model moves to **Metal (MPS)** without configuration. What separates this from a research drop is the delivery. Because the package is on PyPI, `uvx muscriptor transcribe path/to/audio.wav` runs a transcription with **no repository clone at all**, and `uvx muscriptor serve` starts the same web UI that Kyutai hosts at muscriptor.kyutai.org, complete with a live piano roll. The CLI's **`--format sheets`** flag goes a step further than MIDI and engraves actual readable notation: the output directory gets `score.mid`, `score.musicxml`, a `full_score.pdf` with every instrument on one system, then **one PDF per instrument plus a tablature PDF for fretted ones** — electric guitar, electric bass, drum kit, each split out. That path needs **MuseScore 4 or newer** installed separately. Platform handling is unusually careful for a model repo. Windows users need `--torch-backend=cu128` to get off the CPU default; Intel Macs need `--python 3.12` pinned, because PyTorch stopped shipping x86_64 wheels after torch 2.2.2. Both quirks are documented in a table rather than left in the issue tracker. Two caveats matter before adopting it. First, and most important, **the code and the weights are not under the same license**: the repository is **MIT**, but the model weights on HuggingFace are **CC BY-NC 4.0 — non-commercial only**. Anyone planning a paid product around this needs to resolve licensing with Kyutai first, and the distinction is easy to miss when GitHub's sidebar simply reads "MIT." Second, the weights are **gated**: you have to log into HuggingFace and accept the license on each model page before `uvx` can pull anything, so there is no fully anonymous install path, and CI or air-gapped setups need an `HF_TOKEN` provisioned in advance.