Update app.py

🧪 use radames/sdxl-turbo-DPO-LoRA

app.py

@@ -6,16 +6,22 @@ import random
 from diffusers import DiffusionPipeline
 import torch
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "radames/sdxl-turbo-DPO-LoRA"  # Replace to the model you would like to use
+model_repo_id = "stabilityai/sdxl-turbo"  # Base model
+lora_adapter_id = "radames/sdxl-turbo-DPO-LoRA"  # LoRA adapter
+lora_adapter_name = "dpo-lora-sdxl-turbo"
 
 if torch.cuda.is_available():
     torch_dtype = torch.float16
+    device = "cuda"
 else:
     torch_dtype = torch.float32
+    device = "cpu"
 
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype, variant="fp16" if torch_dtype==torch.float16 else None)
 pipe = pipe.to(device)
+# Charger l'adapter LoRA
+pipe.load_lora_weights(lora_adapter_id, adapter_name=lora_adapter_name)
+pipe.set_adapters([lora_adapter_name], adapter_weights=[1.0])
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024