diff --git a/docs/source/en/api/pipelines/audioldm.mdx b/docs/source/en/api/pipelines/audioldm.mdx index f3987d2263ac..25a5bb8bce13 100644 --- a/docs/source/en/api/pipelines/audioldm.mdx +++ b/docs/source/en/api/pipelines/audioldm.mdx @@ -25,14 +25,14 @@ This pipeline was contributed by [sanchit-gandhi](https://huggingface.co/sanchit ## Text-to-Audio -The [`AudioLDMPipeline`] can be used to load pre-trained weights from [cvssp/audioldm](https://huggingface.co/cvssp/audioldm) and generate text-conditional audio outputs: +The [`AudioLDMPipeline`] can be used to load pre-trained weights from [cvssp/audioldm-s-full-v2](https://huggingface.co/cvssp/audioldm-s-full-v2) and generate text-conditional audio outputs: ```python from diffusers import AudioLDMPipeline import torch import scipy -repo_id = "cvssp/audioldm" +repo_id = "cvssp/audioldm-s-full-v2" pipe = AudioLDMPipeline.from_pretrained(repo_id, torch_dtype=torch.float16) pipe = pipe.to("cuda") @@ -56,7 +56,7 @@ Inference: ### How to load and use different schedulers The AudioLDM pipeline uses [`DDIMScheduler`] scheduler by default. But `diffusers` provides many other schedulers -that can be used with the AudioLDM pipeline such as [`PNDMScheduler`], [`LMSDiscreteScheduler`], [`EulerDiscreteScheduler`], +that can be used with the AudioLDM pipeline such as [`PNDMScheduler`], [`LMSDiscreteScheduler`], [`EulerDiscreteScheduler`], [`EulerAncestralDiscreteScheduler`] etc. We recommend using the [`DPMSolverMultistepScheduler`] as it's currently the fastest scheduler there is. @@ -68,12 +68,14 @@ method, or pass the `scheduler` argument to the `from_pretrained` method of the >>> from diffusers import AudioLDMPipeline, DPMSolverMultistepScheduler >>> import torch ->>> pipeline = AudioLDMPipeline.from_pretrained("cvssp/audioldm", torch_dtype=torch.float16) +>>> pipeline = AudioLDMPipeline.from_pretrained("cvssp/audioldm-s-full-v2", torch_dtype=torch.float16) >>> pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config) >>> # or ->>> dpm_scheduler = DPMSolverMultistepScheduler.from_pretrained("cvssp/audioldm", subfolder="scheduler") ->>> pipeline = AudioLDMPipeline.from_pretrained("cvssp/audioldm", scheduler=dpm_scheduler, torch_dtype=torch.float16) +>>> dpm_scheduler = DPMSolverMultistepScheduler.from_pretrained("cvssp/audioldm-s-full-v2", subfolder="scheduler") +>>> pipeline = AudioLDMPipeline.from_pretrained( +... "cvssp/audioldm-s-full-v2", scheduler=dpm_scheduler, torch_dtype=torch.float16 +... ) ``` ## AudioLDMPipeline