Update README.md

README.md

@@ -8,6 +8,7 @@
 pipeline = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype = torch.float16)
 pipeline = pipeline.to('cuda')
 pipeline.scheduler = LCMScheduler.from_config(pipeline.scheduler.config)
+pipeline.load_lora_weights('Yihong666/yoso_sd1.5_lora')
 generator = torch.manual_seed(318)
 steps = 1
 bs = 1
@@ -25,12 +26,30 @@ imgs= pipeline(prompt="A photo of a dog",
 imgs
 ```
 
+The simple inference without informative initialization, but worse quality:
+```python
+pipeline = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype = torch.float16)
+pipeline = pipeline.to('cuda')
+pipeline.scheduler = LCMScheduler.from_config(pipeline.scheduler.config)
+pipeline.load_lora_weights('Yihong666/yoso_sd1.5_lora')
+generator = torch.manual_seed(318)
+steps = 1
+imgs_noise = pipeline(prompt="A photo of a corgi in forest, highly detailed, 8k, XT3.",
+                    num_inference_steps=1, 
+                    num_images_per_prompt = 1,
+                        generator = generator,
+                        guidance_scale=1.,
+                   )[0]
+imgs_noise[0]
+```
+
 ### 2-step inference
 We note that a small CFG can be used to enhance the image quality.
 ```python
 pipeline = DiffusionPipeline.from_pretrained("stablediffusionapi/realistic-vision-v51", torch_dtype = torch.float16)
 pipeline = pipeline.to('cuda')
 pipeline.scheduler = LCMScheduler.from_config(pipeline.scheduler.config)
+pipeline.load_lora_weights('Yihong666/yoso_sd1.5_lora')
 generator = torch.manual_seed(318)
 steps = 2
 imgs= pipeline(prompt="A photo of a man, XT3",