Instructions to use Muapi/w-w-chain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/w-w-chain with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cocktailpeanut/pony-diffusion-v6-xl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/w-w-chain") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 6d6962ff2787022b9ce4cd2c936f49770251dd48df7e402425fdd0e86df0ecdc
- Size of remote file:
- 1.86 MB
- SHA256:
- 3f0e866a6725d26f970108ff4eb1e17fa6bb688c4642cbf6a9477029f02ecda3
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