half precision set to false

app.py

@@ -77,7 +77,6 @@ def generate_interpolated_images(obj1, obj2):
     size2 = json.loads(obj2['size'])
     prompt2_c = (torch.from_numpy(arr2.reshape(size2))).float().cuda()
 
-
     images = []
     for j in range(1, dist_frames):
         

sd.py

@@ -47,7 +47,7 @@ from ldm.models.diffusion.ddim import DDIMSampler
 from ldm.models.diffusion.plms import PLMSSampler
 
 # 2. Set model download config
-def load_model_from_config(config, ckpt, verbose=False, device='cuda', half_precision=True):
+def load_model_from_config(config, ckpt, verbose=False, device='cuda', half_precision=False):
     map_location = "cuda" if torch.cuda.is_available() else "cpu"
     print(f"Loading model from {ckpt}")
     pl_sd = torch.load(ckpt, map_location=map_location)