Instructions to use Muapi/sucking-testicle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/sucking-testicle 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/sucking-testicle") 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:
- 553ab46e69f39aac5f9809e4ee36d9970d78b0ccda75b71c4c78989633f085c7
- Size of remote file:
- 4.15 MB
- SHA256:
- acae7bfa88e512f14dc39fa41f4f404995d5c0c739c0b8a51e0ce151805b2a55
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