@@ -25,14 +25,14 @@ This pipeline was contributed by [sanchit-gandhi](https://huggingface.co/sanchit
25
25
26
26
## Text-to-Audio
27
27
28
- The [`AudioLDMPipeline`] can be used to load pre-trained weights from [cvssp/audioldm](https://huggingface.co/cvssp/audioldm) and generate text-conditional audio outputs:
28
+ 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:
29
29
30
30
```python
31
31
from diffusers import AudioLDMPipeline
32
32
import torch
33
33
import scipy
34
34
35
- repo_id = " cvssp/audioldm"
35
+ repo_id = " cvssp/audioldm-s-full-v2 "
36
36
pipe = AudioLDMPipeline.from_pretrained(repo_id, torch_dtype =torch.float16)
37
37
pipe = pipe.to("cuda")
38
38
@@ -56,7 +56,7 @@ Inference:
56
56
### How to load and use different schedulers
57
57
58
58
The AudioLDM pipeline uses [`DDIMScheduler`] scheduler by default. But `diffusers` provides many other schedulers
59
- that can be used with the AudioLDM pipeline such as [`PNDMScheduler`], [`LMSDiscreteScheduler`], [`EulerDiscreteScheduler`],
59
+ that can be used with the AudioLDM pipeline such as [`PNDMScheduler`], [`LMSDiscreteScheduler`], [`EulerDiscreteScheduler`],
60
60
[`EulerAncestralDiscreteScheduler`] etc. We recommend using the [`DPMSolverMultistepScheduler`] as it's currently the fastest
61
61
scheduler there is.
62
62
@@ -68,12 +68,14 @@ method, or pass the `scheduler` argument to the `from_pretrained` method of the
68
68
>>> from diffusers import AudioLDMPipeline, DPMSolverMultistepScheduler
69
69
>>> import torch
70
70
71
- >>> pipeline = AudioLDMPipeline .from_pretrained (" cvssp/audioldm" , torch_dtype =torch .float16 )
71
+ >>> pipeline = AudioLDMPipeline .from_pretrained (" cvssp/audioldm-s-full-v2 " , torch_dtype =torch .float16 )
72
72
>>> pipeline .scheduler = DPMSolverMultistepScheduler .from_config (pipeline .scheduler .config )
73
73
74
74
>>> # or
75
- >>> dpm_scheduler = DPMSolverMultistepScheduler .from_pretrained (" cvssp/audioldm" , subfolder =" scheduler" )
76
- >>> pipeline = AudioLDMPipeline .from_pretrained (" cvssp/audioldm" , scheduler =dpm_scheduler , torch_dtype =torch .float16 )
75
+ >>> dpm_scheduler = DPMSolverMultistepScheduler .from_pretrained (" cvssp/audioldm-s-full-v2" , subfolder =" scheduler" )
76
+ >>> pipeline = AudioLDMPipeline .from_pretrained (
77
+ ... " cvssp/audioldm-s-full-v2" , scheduler =dpm_scheduler , torch_dtype =torch .float16
78
+ ... )
77
79
` ` `
78
80
79
81
## AudioLDMPipeline
0 commit comments