MiDashengLM-Gen generates blended 16 kHz mono audio scenes — speech, music,
sound effects and ambience in one pass — from a structured multi-view caption
(
<|caption|> <|asr|> <|speech|> <|sfx|> <|music|> <|env|>
), 1–20 s,
via Qwen3-1.7B + per-token conditional flow matching + a Vocos vocoder.
Differences from upstream
Precision
: weights may be cast fp32 → bf16 (one
model.safetensors
);
NOTICE
records the payload precision and per-file sha256 digests.
Upstream fp32 was sha256-verified against the hub before casting, and a
bf16 payload is published only after an A/B parity pass on GPU.
Bundled tokenizer
:
tokenizer/
carries the Qwen3-1.7B tokenizer +
config pinned at the revision recorded in
tokenizer/tokens_added.json
(upstream fetches it from the network, unpinned, at construction time).
tokens_added.json
also records the 28 special tokens appended in
training order — loader drift fails loudly instead of generating noise.
No remote code
: the
modeling_*.py
trust-remote-code files are not
mirrored; MAESTRO vendors the inference code (Apache-2.0) in-tree.
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