moss-audio-models / README.md
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---
license: apache-2.0
base_model: OpenMOSS-Team/MOSS-Audio-4B-Instruct
tags:
- audio
- audio-text-to-text
- maestro
---
# MOSS-Audio 4B — MAESTRO mirror
Verbatim mirror of
[OpenMOSS-Team/MOSS-Audio-4B-Instruct](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-4B-Instruct)
(revision `6907a499dc0e87cc77c8ae0fe23fd0eb5476a02d`, 2026-04) packaged for the
MAESTRO DAW's offline runtime.
MOSS-Audio 4B-Instruct (OpenMOSS) is a general audio-understanding LLM —
a Whisper-style audio encoder feeding a Qwen3-4B language model with DeepStack
feature injection. It captions any recording (speech, sounds, music),
transcribes speech with timestamps, reports on speakers and their emotional
state, lists sound events, and answers free-form questions about the audio.
## Layout
```
bf16/ everything MAESTRO downloads (manifest allow_patterns)
model-0000{1..3}-of-00003.safetensors bf16 shards, byte-identical to upstream
model.safetensors.index.json
config.json generation_config.json
tokenizer_config.json vocab.json merges.txt added_tokens.json
special_tokens_map.json processor_config.json chat_template.jinja
sha256.json per-file hashes of this folder
README.md this file
```
## Differences from upstream
- The remote-code Python files (`configuration_moss_audio.py`,
`processing_moss_audio.py`) are **not** shipped: MAESTRO vendors the
upstream GitHub `src/` inference package
(github.com/OpenMOSS/MOSS-Audio @ `ce783cb7`) and never uses
`trust_remote_code`. (Upstream's weights repo ships no modeling file at
all — the GitHub package is the actual torch implementation.)
- The `assets/` figures and upstream README are not shipped.
- Weight shards are byte-identical to upstream (sha256-verified against the
upstream LFS metadata at mirror time — see `bf16/sha256.json`).
## License
Apache-2.0, same as upstream code and weights. Copyright the OpenMOSS team.
This mirror exists so MAESTRO installs pull a pinned, verified snapshot; all
credit for the model goes to its authors.