Instructions to use JosephusCheung/RuminationDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JosephusCheung/RuminationDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JosephusCheung/RuminationDiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece, best quality, anime, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, garden, looking at viewer" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("JosephusCheung/RuminationDiffusion", dtype=torch.bfloat16, device_map="cuda")
prompt = "masterpiece, best quality, anime, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, garden, looking at viewer"
image = pipe(prompt).images[0]This is only a test model, not recommended, please don't use it directly!
Fine-tuned off Stable Diffusion v2-1_768-nonema-pruned.ckpt.
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