124 lines
4.2 KiB
YAML
124 lines
4.2 KiB
YAML
# Universal TTS benchmark model registry.
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# Maps HuggingFace model ID → supported tasks + per-task extra body fields.
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# To add a new TTS model: add an entry here. No code changes required.
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#
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# The server auto-loads its Deploy YAML from vllm_omni/deploy/<model>.yaml via
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# the Pipeline + Deploy schema introduced in #2383, so no stage_config path
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# is tracked here.
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models:
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# -CustomVoice checkpoints lack speaker_encoder weights, so voice_clone is
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# NOT supported (an attempt raises ValueError from _extract_speaker_embedding
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# at model runtime). Use -Base for voice_clone.
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Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice:
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supported_tasks: [default_voice, voice_design]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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trust_remote_code: true
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task_extra_body:
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default_voice:
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voice: Vivian
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language: English
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task_type: CustomVoice
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voice_design:
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task_type: VoiceDesign
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language: English
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Qwen/Qwen3-TTS-12Hz-1.7B-Base:
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supported_tasks: [voice_clone]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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trust_remote_code: true
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task_extra_body:
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voice_clone:
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task_type: Base
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bosonai/higgs-audio-v3-tts-4b:
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supported_tasks: [default_voice, voice_clone]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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trust_remote_code: true
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task_extra_body:
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default_voice: {}
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voice_clone: {}
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openbmb/VoxCPM2:
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supported_tasks: [voice_clone, default_voice]
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trust_remote_code: true
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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trust_remote_code: true
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task_extra_body:
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voice_clone: {}
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default_voice:
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voice: default
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# MOSS-TTS family. After the serving_speech.py variant-detection refactor
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# all five variants now go through OpenAI /v1/audio/speech with the
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# variant-specific request fields (ambient_sound, ref_audio_2, instructions).
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OpenMOSS-Team/MOSS-TTS:
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supported_tasks: [voice_clone]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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task_extra_body:
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voice_clone: {}
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# MOSS-TTS-v1.5: continued-training upgrade of MOSS-TTS 1.0 — same
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# MossTTSDelay-8B architecture and API, so identical wiring. Adds 31-language
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# synthesis via the `language` field and inline `[pause Xs]` markers.
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OpenMOSS-Team/MOSS-TTS-v1.5:
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supported_tasks: [voice_clone]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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task_extra_body:
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voice_clone: {}
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OpenMOSS-Team/MOSS-TTS-Realtime:
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supported_tasks: [voice_clone]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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task_extra_body:
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voice_clone: {}
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# MOSS-TTS-Local-Transformer-v1.5: Qwen3 backbone + 1-layer GPT2-style local
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# depth transformer (n_vq=12), paired with the 48 kHz stereo
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# MOSS-Audio-Tokenizer-v2 codec. Same voice-clone request shape as the
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# other MOSS-TTS variants.
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OpenMOSS-Team/MOSS-TTS-Local-Transformer-v1.5:
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supported_tasks: [voice_clone]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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task_extra_body:
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voice_clone: {}
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# MOSS-TTSD synthesizes [S1]/[S2] dialogue. The seed-tts voice_clone dataset
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# has single-speaker rows; bench piggybacks on it (both speakers share the
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# same ref_audio). For real dialogue evaluation use the ttsd dataset.
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OpenMOSS-Team/MOSS-TTSD-v1.0:
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supported_tasks: [voice_clone, dialogue]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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task_extra_body:
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voice_clone: {}
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dialogue: {}
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# MOSS-SoundEffect ignores text/ref_audio; expects ambient_sound +
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# duration_seconds. The sound_effect dataset module emits those.
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OpenMOSS-Team/MOSS-SoundEffect:
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supported_tasks: [sound_effect]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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task_extra_body:
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sound_effect:
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duration_seconds: 10
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# MOSS-VoiceGenerator: instructions-driven (no ref_audio). seed-tts-design
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# dataset already emits {instructions, target_text}, so voice_design works
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# out of the box once the serving validator accepts instructions.
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OpenMOSS-Team/MOSS-VoiceGenerator:
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supported_tasks: [voice_design]
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backend: openai-audio-speech
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endpoint: /v1/audio/speech
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task_extra_body:
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voice_design: {}
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