59 lines
1.7 KiB
Markdown
59 lines
1.7 KiB
Markdown
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# Documentation
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- Class name: SaltAudioLDM2LoadModel
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- Category: SALT/Audio/AudioLDM2
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- Output node: False
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这个节点旨在从预定义的模型集中加载特定的音频模型。它有助于初始化针对音频潜在扩散任务优化设置的音频模型，确保模型为进一步的音频处理或生成任务做好准备。
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# Input types
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## Required
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- model
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- 指定要加载的模型，从预定义的音频潜在扩散模型列表中选择。此选择决定了加载模型的特定音频处理能力和特征。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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## Optional
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- device
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- 确定加载模型的计算设备（'cuda'或'cpu'），影响性能和效率。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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# Output types
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- audioldm2_model
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- 加载的音频潜在扩散模型，可用于音频处理或生成任务。
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- Comfy dtype: AUDIOLDM_MODEL
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- Python dtype: AudioLDM2Pipeline
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## Usage tips
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- Infra type: `GPU`
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- Common nodes: unknown
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## Source code
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```python
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class SaltAudioLDM2LoadModel:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"model": (["cvssp/audioldm2", "cvssp/audioldm2-large", "cvssp/audioldm2-music"], ),
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},
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"optional": {
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"device": (["cuda", "cpu"], ),
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},
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}
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RETURN_TYPES = ("AUDIOLDM_MODEL", )
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RETURN_NAMES = ("audioldm2_model", )
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FUNCTION = "load_model"
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CATEGORY = "SALT/Audio/AudioLDM2"
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def load_model(self, model, device="cuda"):
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models = folder_paths.models_dir
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audioldm2_models = os.path.join(models, "AudioLDM2")
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return (AudioLDM2Pipeline.from_pretrained(model, cache_dir=audioldm2_models, torch_dtype=torch.float16).to(device), )
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```
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