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
Download example_gifs/tank_squish.gif from Remade-AI/Squish: direct link, hf CLI and curl.
- Browser
- Download file 6.77 MB
-
https://huggingface.co/Remade-AI/Squish/resolve/main/example_gifs/tank_squish.gif
- Command line
-
hf download hf://Remade-AI/Squish/example_gifs/tank_squish.gif
-
curl -L -o tank_squish.gif https://huggingface.co/Remade-AI/Squish/resolve/main/example_gifs/tank_squish.gif
6.77 MB

- Xet hash:
- 6ff0955aceaf41e52d33b3314b1863b2777ce2cab962cc7a3fb7d2c28ea3d424
- Size of remote file:
- 6.77 MB
- SHA256:
- a7af4cd975986fc06db044fc00452eb8be099c21f46947b94968d5cd76ee7589
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