Upload folder using huggingface_hub

app.py

@@ -28,15 +28,12 @@ except ImportError:
         return fn
 
 MODEL_PATH = Path(__file__).resolve().parent / "model_scripted.pt"
-MODEL = None
 
 
-def get_model():
-    global MODEL
-    if MODEL is None:
-        MODEL = torch.jit.load(str(MODEL_PATH), map_location="cpu")
-        MODEL.eval()
-    return MODEL
+def load_model(device: str):
+    model = torch.jit.load(str(MODEL_PATH), map_location=device)
+    model.eval()
+    return model
 
 
 MAX_SIDE = 4096
@@ -59,9 +56,8 @@ def upscale(image, scale: float = 4.0, target_long_side: float = 0.0):
         shrink = MAX_SIDE / float(max(out_w, out_h))
         out_w, out_h = max(1, int(out_w * shrink)), max(1, int(out_h * shrink))
 
-    model = get_model()
     device = "cuda" if torch.cuda.is_available() else "cpu"
-    model.to(device)
+    model = load_model(device)
 
     lr = torch.from_numpy(np.asarray(img, dtype=np.float32) / 255.0).permute(2, 0, 1).contiguous().unsqueeze(0).to(device)
     with torch.no_grad():

config.json

@@ -49,7 +49,7 @@
   },
   "export": {
     "torch_version": "2.14.1+cu130",
-    "exported_at": "2026-10-23T14:25:12+00:00",
+    "exported_at": "2026-10-23T14:46:57+00:00",
     "method": "torch.jit.script + torch.jit.freeze",
     "verification": {
       "checks": [

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7d9a31c1070c7c283c80dbe530fd763d5327d0b1b9a7293cc5881b972dfe042b
+oid sha256:d5f0b33a4448f4c936d26f05df6f2421566343b4f1abb0701582d8a200b94d4b
 size 5054380