Image-to-Video
Diffusers
Safetensors
English
Chinese
vace
video generation
video-to-video editing
refernce-to-video
Instructions to use Wan-AI/Wan2.1-VACE-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-VACE-14B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-VACE-14B", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Updated it to work with 1.3 B preview code
#1
by HarshvardhanCn01 - opened
- config.json +1 -1
config.json
CHANGED
|
@@ -6,7 +6,7 @@
|
|
| 6 |
"ffn_dim": 13824,
|
| 7 |
"freq_dim": 256,
|
| 8 |
"in_dim": 16,
|
| 9 |
-
"model_type": "
|
| 10 |
"num_heads": 40,
|
| 11 |
"num_layers": 40,
|
| 12 |
"out_dim": 16,
|
|
|
|
| 6 |
"ffn_dim": 13824,
|
| 7 |
"freq_dim": 256,
|
| 8 |
"in_dim": 16,
|
| 9 |
+
"model_type": "t2v",
|
| 10 |
"num_heads": 40,
|
| 11 |
"num_layers": 40,
|
| 12 |
"out_dim": 16,
|