update app.py to link space and models

app.py

@@ -10,7 +10,9 @@ import torch
 import torchvision
 import gradio as gr
 import numpy as np
+
 from gradio.components import Textbox, Video
+from huggingface_hub import hf_hub_download
 
 from utils.common_utils import load_model_checkpoint
 from utils.utils import instantiate_from_config
@@ -144,7 +146,9 @@ if __name__ == "__main__":
     config = OmegaConf.load("configs/inference_t2v_512_v2.0.yaml")
     model_config = config.pop("model", OmegaConf.create())
     pretrained_t2v = instantiate_from_config(model_config)
-    pretrained_t2v = load_model_checkpoint(pretrained_t2v, "checkpoints/VideoCrafter2_model.ckpt")
+
+    pretrained_path = hf_hub_download("VideoCrafter/VideoCrafter2", filename="model.ckpt")
+    pretrained_t2v = load_model_checkpoint(pretrained_t2v, pretrained_path)
     
     unet_config = model_config["params"]["unet_config"]
     unet_config["params"]["use_checkpoint"] = False
@@ -153,7 +157,8 @@ if __name__ == "__main__":
 
     unet = instantiate_from_config(unet_config)
 
-    unet.load_state_dict(torch.load("checkpoints/unet_mg.pt", map_location=device))
+    unet_path = hf_hub_download(repo_id="jiachenli-ucsb/T2V-Turbo-v2", filename="unet_mg.pt")
+    unet.load_state_dict(torch.load(unet_path, map_location=device))
     unet.eval()
 
     pretrained_t2v.model.diffusion_model = unet

checkpoints/VideoCrafter2_model.ckpt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1edf769ece3308e977228943eeeed39286806aba9da17350449a3fbf4324ccfb
-size 7404653244

checkpoints/unet_mg.pt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:92c8767b40a5b2737dd3c69f5f13dae222ead5bd4befbbf894ca870231db13bc
-size 5655143958