Update README.md

README.md

@@ -22,25 +22,35 @@ Kolors is a large-scale text-to-image generation model based on latent diffusion
 
 ## 🚀 Quick Start
 ### Using with Diffusers
-Make sure you upgrade to the latest version of diffusers: `pip install -U diffusers`. And then you can run:
+Make sure you upgrade to the latest version of diffusers==0.30.0.dev0: 
+```
+git clone https://github.com/huggingface/diffusers
+cd diffusers
+python3 setup.py install
+```
+**Notes:**
+- The pipeline uses the `EulerDiscreteScheduler` by default. We recommend using this scheduler with `guidance scale=5.0` and `num_inference_steps=50`.
+- The pipeline also supports the `EDMDPMSolverMultistepScheduler`. `guidance scale=5.0` and `num_inference_steps=25` is a good default for this scheduler.
+
+And then you can run:
 ```python
 import torch
+
 from diffusers import KolorsPipeline
 
 pipe = KolorsPipeline.from_pretrained(
-    "Kwai-Kolors/Kolors-diffusers",
-    torch_dtype=torch.float16,
-    variant='fp16',
-    trust_remote_code=True,
-    force_zeros_for_empty_prompt=False,)
-pipe = pipe.to("cuda")
+    "Kwai-Kolors/Kolors-diffusers", 
+    torch_dtype=torch.float16, 
+    variant="fp16"
+).to("cuda")
+
+prompt = '一张瓢虫的照片，微距，变焦，高质量，电影，拿着一个牌子，写着"可图"'
 
 image = pipe(
-    "一张瓢虫的照片，微距，变焦，高质量，电影，拿着一个牌子，写着“可图”",
-    height=1024,
-    width=1024,
-    num_inference_steps=50,
+    prompt=prompt,
+    negative_prompt="",
     guidance_scale=5.0,
+    num_inference_steps=50,
     generator=torch.Generator(pipe.device).manual_seed(66),
 ).images[0]
 image.show()