Upload app.py

app.py

@@ -3,6 +3,7 @@ import numpy as np
 import random
 
 from diffusers import DiffusionPipeline
+from peft import PeftModel, PeftConfig
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -39,10 +40,8 @@ def load_pipeline(model_id: str):
         base_model = "CompVis/stable-diffusion-v1-4"
         pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch_dtype)
         # Load the LoRA weights into the U-Net.
-        # This assumes that load_attn_procs loads the LoRA weights.
-        # pipe.unet.load_attn_procs(model_id)
-        pipe.load_lora_weights(model_id, weight_name="text_encoder/adapter_model.safetensors")
-        pipe.load_lora_weights(model_id, weight_name="unet/adapter_model.safetensors")
+        pipe.unet = PeftModel.from_pretrained(pipe.unet, "unet")
+
     else:
         pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)