Update app.py

app.py

@@ -112,7 +112,7 @@ pipeline.scheduler = EulerAncestralDiscreteScheduler.from_config(
 )
 
 # load custom white-background UNet
-unet_ckpt_path = hf_hub_download(repo_id="TencentARC/InstantMesh", filename="diffusion_pytorch_model.bin", repo_type="model")
+unet_ckpt_path = hf_hub_download(repo_id="jkorstad/InstantMesh", filename="diffusion_pytorch_model.bin", repo_type="model")
 state_dict = torch.load(unet_ckpt_path, map_location='cpu')
 pipeline.unet.load_state_dict(state_dict, strict=True)
 
@@ -120,7 +120,7 @@ pipeline = pipeline.to(device)
 
 # load reconstruction model
 print('Loading reconstruction model ...')
-model_ckpt_path = hf_hub_download(repo_id="TencentARC/InstantMesh", filename="instant_mesh_large.ckpt", repo_type="model")
+model_ckpt_path = hf_hub_download(repo_id="jkorstad/InstantMesh", filename="instant_mesh_large.ckpt", repo_type="model")
 model = instantiate_from_config(model_config)
 state_dict = torch.load(model_ckpt_path, map_location='cpu')['state_dict']
 state_dict = {k[14:]: v for k, v in state_dict.items() if k.startswith('lrm_generator.') and 'source_camera' not in k}