Update app.py

app.py

@@ -3,10 +3,10 @@ import torch
 import os
 from diffusers import StableDiffusion3Pipeline
 from safetensors.torch import load_file
-from spaces import GPU  # Remove this line if NOT in a HF Space
+from spaces import GPU  # Remove if not in HF Space
 
 # 1. Define model ID and HF_TOKEN (at the VERY beginning)
-model_id = "stabilityai/stable-diffusion-3.5-large"  # Correct model ID for SD 3.5 Large
+model_id = "stabilityai/stable-diffusion-3.5-large"  # Or your preferred model ID
 hf_token = os.getenv("HF_TOKEN")  # For private models (set in HF Space settings)
 
 # 2. Initialize pipeline (to None initially)
@@ -14,12 +14,18 @@ pipeline = None
 
 # 3. Load Stable Diffusion and LoRA (before Gradio)
 try:
-    pipeline = StableDiffusion3Pipeline.from_pretrained(
-        model_id,
-        use_auth_token=hf_token,
-        torch_dtype=torch.float16,  # Use float16 for memory efficiency
-        cache_dir="./model_cache"  # For caching
-    )
+    if hf_token: # check if the token exists, if not, then do not pass the token
+        pipeline = StableDiffusion3Pipeline.from_pretrained(
+            model_id,
+            torch_dtype=torch.float16,
+            cache_dir="./model_cache"  # For caching
+        )
+    else:
+        pipeline = StableDiffusion3Pipeline.from_pretrained(
+            model_id,
+            torch_dtype=torch.float16,
+            cache_dir="./model_cache"  # For caching
+        )
 
     lora_filename = "lora_trained_model.safetensors"  # EXACT filename of your LoRA
     lora_path = os.path.join("./", lora_filename)