SD3 support

app.py

@@ -19,7 +19,7 @@ MODEL_MAP = {
     "SD 3": "stabilityai/stable-diffusion-3-medium-diffusers",
 }
 RESOLUTION_MAP = { "SD 1.5": 512, "SD 2.1": 768, "SDXL": 1024, "SD 3": 1024 }
-SEED_MAP = { "SD 1.5": 850728, "SD 2.1": 944905, "SDXL": 178914170, "SD 3": 282386105 }
+SEED_MAP = { "SD 1.5": 850728, "SD 2.1": 944905, "SDXL": 450040818, "SD 3": 282386105 }
 TAG_SCALE_MAP = {
     "SD 1.5": 1.15, # 기본값
     "SD 2.1": 1.15, # 기본값
@@ -47,7 +47,12 @@ def load_pipeline(model_name, progress):
     model_id = MODEL_MAP[model_name]
     pipeline_class = PIPELINE_MAP[model_name]
     progress(0, desc=f"Loading model: {model_id} with {pipeline_class.__name__}...")
-    pipe = pipeline_class.from_pretrained(model_id, torch_dtype=torch_dtype)
+    if model_name == "SD 3": 
+        pipe = pipeline_class.from_pretrained(model_id, torch_dtype=torch_dtype, 
+            text_encoder_3=None, 
+            tokenizer_3=None,)
+    else:
+        pipe = pipeline_class.from_pretrained(model_id, torch_dtype=torch_dtype)
     pipe = pipe.to(device)
     current_model_id = model_id
     progress(1)
@@ -89,7 +94,7 @@ def infer(
         seed = random.randint(0, MAX_SEED)
 
     generator_custom = torch.Generator(device=device).manual_seed(int(seed))
-    generator_fixed = torch.Generator(device=device).manual_seed(int(seed))
+    generator_fixed  = torch.Generator(device=device).manual_seed(int(seed))
     
     unconditional_prompt = ""