Update app.py
Browse files
app.py
CHANGED
@@ -1,15 +1,27 @@
|
|
1 |
import streamlit as st
|
2 |
-
|
3 |
-
# x = st.slider('Select a value')
|
4 |
-
# st.write(x, 'squared is', x * x)
|
5 |
import torch
|
6 |
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
|
7 |
from diffusers.utils import export_to_video
|
8 |
|
9 |
-
|
10 |
-
|
11 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
12 |
|
13 |
prompt = "Pop international experimental music"
|
14 |
-
|
|
|
|
|
|
|
|
|
15 |
video_path = export_to_video(video_frames)
|
|
|
1 |
import streamlit as st
|
|
|
|
|
|
|
2 |
import torch
|
3 |
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
|
4 |
from diffusers.utils import export_to_video
|
5 |
|
6 |
+
# Explicitly set the device to CPU
|
7 |
+
device = torch.device("cpu")
|
8 |
+
|
9 |
+
# Load the model onto the CPU
|
10 |
+
pipe = DiffusionPipeline.from_pretrained(
|
11 |
+
"damo-vilab/text-to-video-ms-1.7b",
|
12 |
+
torch_dtype=torch.float32 # Use float32 for CPU
|
13 |
+
).to(device)
|
14 |
+
|
15 |
+
# Set the scheduler to use CPU
|
16 |
+
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config).to(device)
|
17 |
+
|
18 |
+
# Disable model offloading if running on CPU
|
19 |
+
# pipe.enable_model_cpu_offload() # This line should be removed or commented out
|
20 |
|
21 |
prompt = "Pop international experimental music"
|
22 |
+
|
23 |
+
# Generate the video frames on the CPU
|
24 |
+
video_frames = pipe(prompt, num_inference_steps=25, device=device).frames
|
25 |
+
|
26 |
+
# Export the frames to a video file
|
27 |
video_path = export_to_video(video_frames)
|