MusicLDMPipeline  
Pipeline for text-to-audio generation using MusicLDM.  
This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods
implemented for all pipelines (downloading, saving, running on a particular device, etc.).  
Args:
vae ([`AutoencoderKL`]):
Variational Auto-Encoder (VAE) model to encode and decode images to and from latent representations.
text_encoder ([`~transformers.ClapModel`]):
Frozen text-audio embedding model (`ClapTextModel`), specifically the
[laion/clap-htsat-unfused](https://huggingface.co/laion/clap-htsat-unfused) variant.
tokenizer ([`PreTrainedTokenizer`]):
A [`~transformers.RobertaTokenizer`] to tokenize text.
feature_extractor ([`~transformers.ClapFeatureExtractor`]):
Feature extractor to compute mel-spectrograms from audio waveforms.
unet ([`UNet2DConditionModel`]):
A `UNet2DConditionModel` to denoise the encoded audio latents.
scheduler ([`SchedulerMixin`]):
A scheduler to be used in combination with `unet` to denoise the encoded audio latents. Can be one of
[`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
vocoder ([`~transformers.SpeechT5HifiGan`]):
Vocoder of class `SpeechT5HifiGan`.  
- all
- __call__
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/musicldm.md