Instructions to use Remade-AI/Squish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Remade-AI/Squish 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-I2V-14B-480P-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Remade-AI/Squish") prompt = "In the video, a miniature dog is presented. The dog is held in a person's hands. The person then presses on the dog, causing a sq41sh squish effect. The person keeps pressing down on the dog, further showing the sq41sh squish effect." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") output = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Update README.md
Browse files
README.md
CHANGED
|
@@ -26,8 +26,6 @@ This LoRA is trained on the Wan2.1 14B I2V 480p model and allows you to squish a
|
|
| 26 |
|
| 27 |
## Examples
|
| 28 |
|
| 29 |
-
## Examples
|
| 30 |
-
|
| 31 |
<table>
|
| 32 |
<tr>
|
| 33 |
<td align="center" style="padding: 20px; background-color: #f8f9fa; border-radius: 10px;">
|
|
|
|
| 26 |
|
| 27 |
## Examples
|
| 28 |
|
|
|
|
|
|
|
| 29 |
<table>
|
| 30 |
<tr>
|
| 31 |
<td align="center" style="padding: 20px; background-color: #f8f9fa; border-radius: 10px;">
|