Update README.md

README.md

@@ -33,20 +33,21 @@ You should use `platypus` to trigger the image generation.
 
 ```python
 import torch
-from diffusers import DiffusionPipeline
+from diffusers import DiffusionPipeline,DDIMScheduler
+import matplotlib.pyplot as plt
 
 # switch to "mps" for apple devices
-pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
-pipe.load_lora_weights("Mohan-diffuser/lora_platypus_sd_15")
+pipeline = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
+pipeline.load_lora_weights("Mohan-diffuser/lora_platypus_sd_15")
+
+pipeline.scheduler = DDIMScheduler.from_config(pipeline.scheduler.config)
 
 prompt = "platypus"
-image = pipe(prompt).images[0]
+image = pipeline(prompt).images[0]
 ```
 
 ## Varying The LoRA Scale
 ```python
-import matplotlib.pyplot as plt
-
 gen_images=[]
 lora_scales = [0.0,0.2,0.4,0.6,0.8,1.0,1.2,1.4]
 for lora_scale in lora_scales:
@@ -57,7 +58,6 @@ for lora_scale in lora_scales:
                         height=512,
                         width=512,
                         cross_attention_kwargs={"scale": lora_scale},
-                        clip_skip=2,
                         generator=torch.manual_seed(0)
                     ).images[0]