Create app.py

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from diffusers import DiffusionPipeline
+import torch
+
+# Gradio demo function for greeting
+def greet(name):
+    return "Hello " + name + "!!"
+
+# Set up the Gradio interface
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo.launch(share=True)
+
+# Load the Stable Diffusion pipeline
+pipeline = DiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0", 
+    torch_dtype=torch.float16
+).to("cuda")
+
+# Load the LoRA weights
+pipeline.load_lora_weights(
+    "ostris/ikea-instructions-lora-sdxl", 
+    weight_name="ikea_instructions_xl_v1_5.safetensors", 
+    adapter_name="ikea"
+)
+pipeline.load_lora_weights(
+    "lordjia/by-feng-zikai", 
+    weight_name="fengzikai_v1.0_XL.safetensors", 
+    adapter_name="feng"
+)