from_pretrained instead of from_single_file

app.py

@@ -4,20 +4,30 @@ from diffusers import StableDiffusionXLPipeline
 
 # Hub IDs of the weights you just pushed
 BASE_MODEL_REPO  = "SG161222/RealVisXL_V5.0/RealVisXL_V5.0_fp16.safetensors"   # or a public ID
-BASE_URL = (
-    "https://huggingface.co/SG161222/RealVisXL_V5.0/"
-    "resolve/main/RealVisXL_V5.0_fp16.safetensors"
-)
+# BASE_URL = (
+    # "https://huggingface.co/SG161222/RealVisXL_V5.0/"
+    # "resolve/main/RealVisXL_V5.0_fp16.safetensors"
+# )
 LORA_REPO        = "pdbdb/lora-act"
 
 print("⏳ Loading SDXL base …")
-pipe = StableDiffusionXLPipeline.from_single_file(
-        BASE_URL,
-        torch_dtype=torch.float16,
-        variant="fp16",
-        add_watermarker=False,
+# pipe = StableDiffusionXLPipeline.from_single_file(
+        # BASE_MODEL_REPO,
+        # torch_dtype=torch.float16,
+        # variant="fp16",
+        # add_watermarker=False,
+# ).to("cuda")
+
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    "SG161222/RealVisXL_V5.0",
+    torch_dtype=torch.float16,
+    variant="fp16",         # picks the *_fp16.safetensors under the hood
+    use_safetensors=True,   # make sure to load safetensors
+    safe_serialization=True,
+    add_watermarker=False,
 ).to("cuda")
 
+
 # ── collect LoRAs from the Hub snapshot ──────────────────────────
 snapshot_path = Path(
     torch.hub.download_url_to_file(  # one-liner cache download