Update app.py

app.py

@@ -1,24 +1,53 @@
 import gradio as gr
 import numpy as np
 import random
-import spaces
 import torch
-from diffusers import DiffusionPipeline, AutoencoderTiny
+import spaces
+from diffusers import (
+    DiffusionPipeline,
+    AutoencoderTiny,
+)
 from huggingface_hub import hf_hub_download
 
-dtype = torch.bfloat16
-device = "cuda" if torch.cuda.is_available() else "cpu"
 
-taef1 = AutoencoderTiny.from_pretrained("aifeifei798/taef1", torch_dtype=dtype).to(device)
-    
-pipe = DiffusionPipeline.from_pretrained("aifeifei798/DarkIdol-flux-v1", torch_dtype=dtype, vae=taef1).to(device)
+def feifeimodload():
 
-pipe.load_lora_weights(hf_hub_download("aifeifei798/feifei-flux-lora-v1", "feifei.safetensors"),adapter_name="feifei")
+    dtype = torch.bfloat16
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    taef1 = AutoencoderTiny.from_pretrained("aifeifei798/taef1", torch_dtype=dtype).to(
+        device
+    )
+    
+    pipe = DiffusionPipeline.from_pretrained(
+        "aifeifei798/DarkIdol-flux-v1", torch_dtype=dtype, vae=taef1
+    ).to(device)
 
-pipe.set_adapters(["feifei"],adapter_weights=[0.65])
+    pipe.load_lora_weights(
+        hf_hub_download("aifeifei798/feifei-flux-lora-v1", "feifei.safetensors"),
+        adapter_name="feifei",
+    )
 
-pipe.fuse_lora(adapter_name=["feifei"],lora_scale=1.0)
+    pipe.load_lora_weights(
+        hf_hub_download(
+            "aifeifei798/feifei-flux-lora-v1", "Shadow-Projection.safetensors"
+        ),
+        adapter_name="Shadow-Projection",
+    )
 
+    pipe.set_adapters(
+        ["feifei","Shadow-Projection"],
+        adapter_weights=[0.75,0.35],
+    )
+    pipe.fuse_lora(
+        adapter_name=["feifei","Shadow-Projection"],
+        lora_scale=1.0,
+    )
+    
+    pipe.unload_lora_weights()
+    torch.cuda.empty_cache()
+    return pipe
+    
+pipe = feifeimodload()
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048