Update README.md

README.md

@@ -54,6 +54,42 @@ image = pipe(prompt, num_inference_steps=4, guidance_scale=0).images[0]
    <img style="width:400px;" src="images/raccoon.png">
 </p>
 
+# Combining Flash Diffusion with Existing LoRAs 🎨
+
+FlashSDXL can also be combined with existing LoRAs to unlock few steps generation in a **training free** manner. It can be integrated straight to Hugging Face pipelines. See an example below.
+
+```python
+from diffusers import DiffusionPipeline, LCMScheduler
+import torch
+
+flash_lora_id = "jasperai/flash-sdxl"
+
+# Load Pipeline
+pipe = DiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
+    variant="fp16"
+)
+
+# Set scheduler
+pipe.scheduler = LCMScheduler.from_config(
+    pipe.scheduler.config
+)
+
+# Load LoRAs
+pipe.load_lora_weights(flash_lora_id, adapter_name="flash")
+pipe.load_lora_weights("TheLastBen/Papercut_SDXL", adapter_name="paper")
+
+pipe.set_adapters(["flash", "paper"], adapter_weights=[1.0, 1.0])
+pipe.to(device="cuda", dtype=torch.float16)
+
+prompt = "papercut, a cute corgi"
+
+image = pipe(prompt, num_inference_steps=4, guidance_scale=0).images[0]
+```
+<p align="center">
+   <img style="width:400px;" src="images/corgi.jpg">
+</p>
+
 # Training Details
 The model was trained for 20k iterations on 4 H100 GPUs (representing approximately a total of 176 GPU hours of training). Please refer to the [paper](http://arxiv.org/abs/2406.02347) for further parameters details.