Instructions to use ShawnHugging/WaymoWAN22NeuralAssets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShawnHugging/WaymoWAN22NeuralAssets with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ShawnHugging/WaymoWAN22NeuralAssets") prompt = "Screenshot" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 62845644ab3ff40db47fc6020e02ae7c73edad1a697cf5df81b4194e2e9317f6
- Size of remote file:
- 1.65 GB
- SHA256:
- 9ff1eee9040c079c46b6830197891f3bc63e10770a4734b5440ddc9abe8475ff
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