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Federico Volovnik-Jose 927c9eb8c0 docs: pin transformers 4.50-4.57 + document language behaviour

After end-to-end testing it became clear MOSS-TTS' remote code is targeted
at a narrow transformers band: <4.50 misses MODALITY_TO_BASE_CLASS_MAPPING
and PreTrainedConfig, >=4.58 starts removing _get_initial_cache_position
and reworking ProcessorMixin internals. 4.50.x is the sweet spot.

- requirements.txt pins transformers >=4.50, <4.58.
- README explains the version constraint and the diagnostic for
  noise-vs-speech output.
- README also notes that the model is Chinese-centric and English
  output without a reference clip will sound Chinese-accented; this is
  upstream model behaviour, not a node bug.

2026-04-27 14:23:51 +02:00

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ComfyUI-MOSS-TTS

ComfyUI custom nodes for MOSS-TTS — a 1.7B parameter zero-shot text-to-speech and voice-cloning model.

Installation

Clone this repo into ComfyUI/custom_nodes/:

cd ComfyUI/custom_nodes
git clone https://github.com/Eutectico/ComfyUI-MOSS-TTS.git

Install Python dependencies (ComfyUI does this automatically on next start, or you can run it manually):
```
pip install -r ComfyUI-MOSS-TTS/requirements.txt
```
Restart ComfyUI. The nodes appear under the MOSS-TTS/ category in the node menu.

The first generation downloads ~13 GB of model weights from HuggingFace. Subsequent runs use the cached weights.

Transformers version

MOSS-TTS' remote code (loaded via trust_remote_code=True) is calibrated for transformers >= 4.50, < 4.58. Earlier releases miss newer APIs the model expects (MODALITY_TO_BASE_CLASS_MAPPING, PreTrainedConfig); later releases (especially the 5.x line) have removed APIs the model still calls (_get_initial_cache_position, etc.). The package contains compatibility shims that paper over a few specific gaps, but staying inside the supported range produces the cleanest results.

If the shipped audio sounds like noise rather than speech, the most common cause is that an unsupported transformers version is installed. Confirm with:

pip show transformers

and pin to a 4.5x version if needed.

Language support

MOSS-TTS was trained primarily on Chinese. Without a voice reference, the default voice tends to render any input with Chinese-leaning phonetics — including English text. For English (or any non-Chinese language) output, supply a clean 5–15 second reference clip in the target language via the MOSS-TTS Voice Reference node.

Nodes

Node	Category	Purpose
`MOSS-TTS Loader`	`MOSS-TTS/loaders`	Loads the model + processor, holds them in a module-level cache.
`MOSS-TTS Voice Reference`	`MOSS-TTS/voice`	Wraps an `AUDIO` input or filesystem path into a voice-reference container.
`MOSS-TTS Generate`	`MOSS-TTS/generation`	Generates speech from text (with optional voice reference).
`MOSS-TTS Unload`	`MOSS-TTS/utility`	Frees the model from VRAM. Optional; place at the end of a workflow if needed.

Quality Presets

The Generate node has a preset dropdown:

Preset	RVQ Layers	Notes
`Custom`	from widgets	Uses the individual sampling sliders as-is.
`Fast (8 RVQ)`	8	Longest audio on T4 (~12 min); lower quality.
`Balanced (16 RVQ)`	16	Default. ~8 min on T4.
`High Quality (24 RVQ)`	24	~5 min on T4.
`Maximum (32 RVQ)`	32	Best quality, ~4 min on T4.

When preset is anything other than Custom, the preset's values override the individual sampling widgets at execution time.

Hardware

Defaults target T4-class GPUs (~16 GB VRAM, FP16, sdpa attention). If you have ≥24 GB VRAM, you may want to set dtype=bf16 and increase max_tokens.

Smoke test

Drop in a MOSS-TTS Loader node (defaults are fine).
Drop in a MOSS-TTS Generate node, connect model and type any text.
Connect audio to Save Audio (built-in).
Run. First run downloads weights (~5–8 min); subsequent runs are fast.

Voice cloning

Connect a Load Audio node → MOSS-TTS Voice Reference → MOSS-TTS Generate.voice. A 5–15 second clean reference clip works well.

Credits

Model: MOSS-TTS by OpenMOSS Team
Source notebook: AIQUEST (MOSS_TTS_Voice_Cloning.ipynb)
ComfyUI integration: this repo

License

MIT — see LICENSE.

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