StableAudioPipeline  
Pipeline for text-to-audio generation using StableAudio.  
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 ([`AutoencoderOobleck`]):
Variational Auto-Encoder (VAE) model to encode and decode images to and from latent representations.
text_encoder ([`~transformers.T5EncoderModel`]):
Frozen text-encoder. StableAudio uses the encoder of
[T5](https://huggingface.co/docs/transformers/model_doc/t5#transformers.T5EncoderModel), specifically the
[google-t5/t5-base](https://huggingface.co/google-t5/t5-base) variant.
projection_model ([`StableAudioProjectionModel`]):
A trained model used to linearly project the hidden-states from the text encoder model and the start and
end seconds. The projected hidden-states from the encoder and the conditional seconds are concatenated to
give the input to the transformer model.
tokenizer ([`~transformers.T5Tokenizer`]):
Tokenizer to tokenize text for the frozen text-encoder.
transformer ([`StableAudioDiTModel`]):
A `StableAudioDiTModel` to denoise the encoded audio latents.
scheduler ([`EDMDPMSolverMultistepScheduler`]):
A scheduler to be used in combination with `transformer` to denoise the encoded audio latents.  
- all
- __call__
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/stable_audio.md