Spaces:
Running
on
L40S
Running
on
L40S
BestWishYsh
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -31,17 +31,21 @@ from models.eva_clip import create_model_and_transforms
|
|
31 |
from models.eva_clip.constants import OPENAI_DATASET_MEAN, OPENAI_DATASET_STD
|
32 |
from models.eva_clip.utils_qformer import resize_numpy_image_long
|
33 |
|
34 |
-
device = "cuda" if torch.cuda.is_available() else "cpu"
|
35 |
|
36 |
-
|
37 |
-
snapshot_download(repo_id="AlexWortega/RIFE", local_dir="model_rife")
|
38 |
-
snapshot_download(repo_id="BestWishYsh/ConsisID-preview", local_dir="BestWishYsh/ConsisID-preview")
|
39 |
|
40 |
-
model_path = "BestWishYsh/ConsisID-preview"
|
41 |
lora_path = None
|
42 |
lora_rank = 128
|
43 |
dtype = torch.bfloat16
|
|
|
44 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
45 |
if os.path.exists(os.path.join(model_path, "transformer_ema")):
|
46 |
subfolder = "transformer_ema"
|
47 |
else:
|
@@ -110,8 +114,12 @@ if "variance_type" in pipe.scheduler.config:
|
|
110 |
pipe.scheduler = CogVideoXDPMScheduler.from_config(pipe.scheduler.config, **scheduler_args)
|
111 |
pipe.to(device)
|
112 |
|
|
|
|
|
113 |
pipe.enable_model_cpu_offload()
|
114 |
pipe.enable_sequential_cpu_offload()
|
|
|
|
|
115 |
|
116 |
os.makedirs("./output", exist_ok=True)
|
117 |
os.makedirs("./gradio_tmp", exist_ok=True)
|
|
|
31 |
from models.eva_clip.constants import OPENAI_DATASET_MEAN, OPENAI_DATASET_STD
|
32 |
from models.eva_clip.utils_qformer import resize_numpy_image_long
|
33 |
|
|
|
34 |
|
35 |
+
model_path = "ckpts"
|
|
|
|
|
36 |
|
|
|
37 |
lora_path = None
|
38 |
lora_rank = 128
|
39 |
dtype = torch.bfloat16
|
40 |
+
device = "cuda" if torch.cuda.is_available() else "cpu"
|
41 |
|
42 |
+
if not os.path.exists(model_path) or not os.path.exists(f"{model_path}/model_real_esran") or not os.path.exists(f"{model_path}/model_rife"):
|
43 |
+
hf_hub_download(repo_id="ai-forever/Real-ESRGAN", filename="RealESRGAN_x4.pth", local_dir=f"{model_path}/model_real_esran")
|
44 |
+
snapshot_download(repo_id="AlexWortega/RIFE", local_dir=f"{model_path}/model_rife")
|
45 |
+
snapshot_download(repo_id="BestWishYsh/ConsisID-preview", local_dir=f"{model_path}")
|
46 |
+
else:
|
47 |
+
print(f"Model already exists in {model_path}, skipping download.")
|
48 |
+
|
49 |
if os.path.exists(os.path.join(model_path, "transformer_ema")):
|
50 |
subfolder = "transformer_ema"
|
51 |
else:
|
|
|
114 |
pipe.scheduler = CogVideoXDPMScheduler.from_config(pipe.scheduler.config, **scheduler_args)
|
115 |
pipe.to(device)
|
116 |
|
117 |
+
# Enable CPU offload for the model.
|
118 |
+
# turn on if you don't have multiple GPUs or enough GPU memory(such as H100) and it will cost more time in inference, it may also reduce the quality
|
119 |
pipe.enable_model_cpu_offload()
|
120 |
pipe.enable_sequential_cpu_offload()
|
121 |
+
# pipe.vae.enable_slicing()
|
122 |
+
# pipe.vae.enable_tiling()
|
123 |
|
124 |
os.makedirs("./output", exist_ok=True)
|
125 |
os.makedirs("./gradio_tmp", exist_ok=True)
|