Instructions to use Remade-AI/Pixar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Remade-AI/Pixar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-T2V-14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Remade-AI/Pixar") prompt = "p1x4r_5ty13 Pixar animation style A small brown puppy with floppy ears sits on a grassy hill, tilting its head curiously at a floating dandelion seed drifting past. Its big, round eyes shine in the soft golden light of the setting sun. The background features rolling hills and a wooden fence." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- Xet hash:
- 2f46617bfc2a9570b176129cb67e0242e2cd2d29981e9ba2ed56953ba9614b71
- Size of remote file:
- 359 MB
- SHA256:
- 0117b1ca731f1c757170d4de1414037dac34d62fbf0f38de178ad3865193e204
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.