Update README.md

README.md

@@ -37,10 +37,8 @@ pip install transformers accelerate safetensors
 ```
 
 **Notes:**
-- The pipeline uses the `EDMEulerScheduler` scheduler. It's an [EDM formulation](https://arxiv.org/abs/2206.00364) of the Euler scheduler.
-- `guidance_scale=5.0` is a good default for this scheduler.
-- The pipeline also supports the `EDMDPMSolverMultistepScheduler` scheduler.  It's an [EDM formulation](https://arxiv.org/abs/2206.00364) of the DPM scheduler.
-- `guidance_scale=3.0` is a good default for this scheduler.
+- The pipeline uses the `EDMEulerScheduler` scheduler by default. It's an [EDM formulation](https://arxiv.org/abs/2206.00364) of the Euler scheduler. `guidance_scale=5.0` is a good default for this scheduler.
+- The pipeline also supports the `EDMDPMSolverMultistepScheduler` scheduler, for crisper fine details. It's an [EDM formulation](https://arxiv.org/abs/2206.00364) of the DPM++ 2M Karras scheduler. `guidance_scale=3.0` is a good default for this scheduler.
 
 Then, run the following snippet:
 
@@ -54,8 +52,12 @@ pipe = DiffusionPipeline.from_pretrained(
     variant="fp16",
 ).to("cuda")
 
+# # Optional: Use DPM++ 2M Karras scheduler for crisper fine details
+# from diffusers import EDMDPMSolverMultistepScheduler
+# pipe.scheduler = EDMDPMSolverMultistepScheduler()
+
 prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
-image = pipe(prompt=prompt, num_inference_steps=50, guidance_scale=7).images[0]
+image = pipe(prompt=prompt, num_inference_steps=50, guidance_scale=3).images[0]
 ```
 
 ### Using the model with Automatic1111/ComfyUI