Instructions to use reneeice/wah with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use reneeice/wah with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("reneeice/wah", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| { | |
| "scheduler": ["diffusers", "KSched", "ddpm"], | |
| "base_model": ["HF", "model_id", "Wan2.2-Fun-A14B-InP"], | |
| "tokenizer": ["transformers", "T5Tokenizer", "tokenizer"], | |
| "text_encoder": ["transformers", "T5EncoderModel", "text_encoder"], | |
| "vae": ["diffusers", "AutoencoderKL", "vae"], | |
| "transformer": ["videox_fun", "Wan2_2Transformer3D", "transformer"] | |
| } | |