Update README.md

README.md

@@ -78,7 +78,7 @@ Anything works as long as it's a multiply of 128.
 # Diffusers
 
 ```shell
-pip install diffusers
+pip install git+https://github.com/Disty0/diffusers@cascade_decoder_sampler
 ```
 
 ```python
@@ -88,22 +88,7 @@ import diffusers
 device = "cuda"
 dtype = torch.float16
 model_path = "/mnt/DataSSD/AI/SoteDiffusion/Wuerstchen3/diffusers/sotediffusion-v2"
-
-
-def get_timestep_ratio_conditioning(t, alphas_cumprod):
-    s = torch.tensor([0.008]) # diffusers uses 0.003 while the original is 0.008
-    clamp_range = [0, 1]
-    min_var = torch.cos(s / (1 + s) * torch.pi * 0.5) ** 2
-    var = alphas_cumprod[t]
-    var = var.clamp(*clamp_range)
-    s, min_var = s.to(var.device), min_var.to(var.device)
-    ratio = (((var * min_var) ** 0.5).acos() / (torch.pi * 0.5)) * (1 + s) - s
-    return ratio
-
-
 pipe = diffusers.AutoPipelineForText2Image.from_pretrained(model_path, text_encoder=None, torch_dtype=dtype)
-pipe.prior_pipe.get_timestep_ratio_conditioning = get_timestep_ratio_conditioning
-pipe.prior_pipe.scheduler.config.clip_sample = False
 
 # de-dupe
 pipe.decoder_pipe.text_encoder = pipe.text_encoder = None # nothing uses this