Files
vllm-omni/vllm_omni/model_executor/models/registry.py
T
2026-05-25 23:16:07 +08:00

278 lines
7.8 KiB
Python

from vllm.model_executor.models.registry import (
_VLLM_MODELS,
_LazyRegisteredModel,
_ModelRegistry,
)
_OMNI_MODELS = {
"Qwen2_5OmniForConditionalGeneration": (
"qwen2_5_omni",
"qwen2_5_omni",
"Qwen2_5OmniForConditionalGeneration",
),
"Qwen2_5OmniThinkerModel": (
"qwen2_5_omni",
"qwen2_5_omni_thinker",
"Qwen2_5OmniThinkerForConditionalGeneration",
),
"Qwen2_5OmniTalkerModel": (
"qwen2_5_omni",
"qwen2_5_omni_talker",
"Qwen2_5OmniTalkerForConditionalGeneration",
),
"Qwen2_5OmniToken2WavModel": (
"qwen2_5_omni",
"qwen2_5_omni_token2wav",
"Qwen2_5OmniToken2WavForConditionalGenerationVLLM",
),
"Qwen2_5OmniToken2WavDiTModel": (
"qwen2_5_omni",
"qwen2_5_omni_token2wav",
"Qwen2_5OmniToken2WavModel",
),
"Qwen2ForCausalLM_old": ("qwen2_5_omni", "qwen2_old", "Qwen2ForCausalLM"), # need to discuss
# Qwen3 Omni MoE models
"Qwen3OmniMoeForConditionalGeneration": (
"qwen3_omni",
"qwen3_omni",
"Qwen3OmniMoeForConditionalGeneration",
),
"Qwen3OmniMoeThinkerForConditionalGeneration": (
"qwen3_omni",
"qwen3_omni_moe_thinker",
"Qwen3OmniMoeThinkerForConditionalGeneration",
),
"Qwen3OmniMoeTalkerForConditionalGeneration": (
"qwen3_omni",
"qwen3_omni_moe_talker",
"Qwen3OmniMoeTalkerForConditionalGeneration",
),
"Qwen3OmniMoeCode2Wav": (
"qwen3_omni",
"qwen3_omni_code2wav",
"Qwen3OmniMoeCode2Wav",
),
"CosyVoice3Model": (
"cosyvoice3",
"cosyvoice3",
"CosyVoice3Model",
),
"OmniVoiceModel": (
"omnivoice",
"omnivoice",
"OmniVoiceModel",
),
"MammothModa2Qwen2ForCausalLM": (
"mammoth_moda2",
"mammoth_moda2",
"MammothModa2Qwen2ForCausalLM",
),
"MammothModa2ARForConditionalGeneration": (
"mammoth_moda2",
"mammoth_moda2",
"MammothModa2ARForConditionalGeneration",
),
"MammothModa2DiTPipeline": (
"mammoth_moda2",
"pipeline_mammothmoda2_dit",
"MammothModa2DiTPipeline",
),
"MammothModa2ForConditionalGeneration": (
"mammoth_moda2",
"mammoth_moda2",
"MammothModa2ForConditionalGeneration",
),
"Mammothmoda2Model": (
"mammoth_moda2",
"mammoth_moda2",
"MammothModa2ForConditionalGeneration",
),
"Qwen3TTSForConditionalGeneration": (
"qwen3_tts",
"qwen3_tts_talker",
"Qwen3TTSTalkerForConditionalGeneration",
),
"Qwen3TTSTalkerForConditionalGeneration": (
"qwen3_tts",
"qwen3_tts_talker",
"Qwen3TTSTalkerForConditionalGeneration",
),
"Qwen3TTSCode2Wav": (
"qwen3_tts",
"qwen3_tts_code2wav",
"Qwen3TTSCode2Wav",
),
## higgs-audio v2
"HiggsAudioV2ForConditionalGeneration": (
"higgs_audio_v2",
"higgs_audio_v2_talker",
"HiggsAudioV2TalkerForConditionalGeneration",
),
"HiggsAudioV2TalkerForConditionalGeneration": (
"higgs_audio_v2",
"higgs_audio_v2_talker",
"HiggsAudioV2TalkerForConditionalGeneration",
),
"HiggsAudioV2Code2WavForConditionalGeneration": (
"higgs_audio_v2",
"higgs_audio_v2_code2wav",
"HiggsAudioV2Code2WavForConditionalGeneration",
),
## mimo_audio
"MiMoAudioModel": (
"mimo_audio",
"mimo_audio",
"MiMoAudioForConditionalGeneration",
),
"MiMoV2ASRForCausalLM": (
"mimo_audio",
"mimo_audio",
"MiMoAudioForConditionalGeneration",
),
"MiMoAudioLLMModel": (
"mimo_audio",
"mimo_audio_llm",
"MiMoAudioLLMForConditionalGeneration",
),
"MiMoAudioToken2WavModel": (
"mimo_audio",
"mimo_audio_code2wav",
"MiMoAudioToken2WavForConditionalGenerationVLLM",
),
## glm_image
"GlmImageForConditionalGeneration": (
"glm_image",
"glm_image_ar",
"GlmImageForConditionalGeneration",
),
## glm_tts
"GLMTTSForConditionalGeneration": (
"glm_tts",
"glm_tts",
"GLMTTSForConditionalGeneration",
),
"OmniBagelForConditionalGeneration": (
"bagel",
"bagel",
"OmniBagelForConditionalGeneration",
),
"HunyuanImage3ForCausalMM": (
"hunyuan_image3",
"hunyuan_image3",
"HunyuanImage3ForConditionalGeneration",
),
## fish_speech (Fish Speech S2 Pro)
"FishSpeechSlowARForConditionalGeneration": (
"fish_speech",
"fish_speech_slow_ar",
"FishSpeechSlowARForConditionalGeneration",
),
"FishSpeechDACDecoder": (
"fish_speech",
"fish_speech_dac_decoder",
"FishSpeechDACDecoder",
),
## VoxCPM2
"VoxCPM2TalkerForConditionalGeneration": (
"voxcpm2",
"voxcpm2_talker",
"VoxCPM2TalkerForConditionalGeneration",
),
## Voxtral TTS
"VoxtralTTSForConditionalGeneration": (
"voxtral_tts",
"voxtral_tts",
"VoxtralTTSForConditionalGeneration",
),
"VoxtralTTSAudioGeneration": (
"voxtral_tts",
"voxtral_tts_audio_generation",
"VoxtralTTSAudioGenerationForConditionalGeneration",
),
"VoxtralTTSAudioTokenizer": ("voxtral_tts", "voxtral_tts_audio_tokenizer", "VoxtralTTSAudioTokenizer"),
## covo_audio
"CovoAudioForCausalLM": (
"covo_audio",
"covo_audio",
"CovoAudioForConditionalGeneration",
),
"CovoAudioForConditionalGeneration": (
"covo_audio",
"covo_audio",
"CovoAudioForConditionalGeneration",
),
"CovoAudioModel": (
"covo_audio",
"covo_audio",
"CovoAudioForConditionalGeneration",
),
"CovoAudioLLMModel": (
"covo_audio",
"covo_audio_llm",
"CovoAudioLLMForConditionalGeneration",
),
"CovoAudioCode2WavModel": (
"covo_audio",
"covo_audio_code2wav",
"CovoAudioCode2WavForConditionalGeneration",
),
## MOSS-TTS-Nano
"MossTTSNanoForCausalLM": (
"moss_tts_nano",
"modeling_moss_tts_nano",
"MossTTSNanoForGeneration",
),
"DyninOmniForConditionalGeneration": (
"dynin_omni",
"dynin_omni",
"DyninOmniForConditionalGeneration",
),
## Ming-flash-omni-2.0
"MingFlashOmniForConditionalGeneration": (
"ming_flash_omni",
"ming_flash_omni",
"MingFlashOmniForConditionalGeneration",
),
"MingFlashOmniThinkerForConditionalGeneration": (
"ming_flash_omni",
"ming_flash_omni_thinker",
"MingFlashOmniThinkerForConditionalGeneration",
),
"MingFlashOmniTalkerForConditionalGeneration": (
"ming_flash_omni",
"ming_flash_omni_talker",
"MingFlashOmniTalkerForConditionalGeneration",
),
# Alias: HF repo currently ships this architecture name in config.json
"BailingMM2NativeForConditionalGeneration": (
"ming_flash_omni",
"ming_flash_omni",
"MingFlashOmniForConditionalGeneration",
),
}
_VLLM_OMNI_MODELS = {
**_VLLM_MODELS,
**_OMNI_MODELS,
}
OmniModelRegistry = _ModelRegistry(
{
**{
model_arch: _LazyRegisteredModel(
module_name=f"vllm.model_executor.models.{mod_relname}",
class_name=cls_name,
)
for model_arch, (mod_relname, cls_name) in _VLLM_MODELS.items()
},
**{
model_arch: _LazyRegisteredModel(
module_name=f"vllm_omni.model_executor.models.{mod_folder}.{mod_relname}",
class_name=cls_name,
)
for model_arch, (mod_folder, mod_relname, cls_name) in _OMNI_MODELS.items()
},
}
)