Instructions to use SidXXD/Clean-f_26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/Clean-f_26 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/Clean-f_26", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a sks person" 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("SidXXD/Clean-f_26", dtype=torch.bfloat16, device_map="cuda")
prompt = "photo of a sks person"
image = pipe(prompt).images[0]Custom Diffusion - SidXXD/Clean-f_26
These are Custom Diffusion adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on photo of a sks person using Custom Diffusion. You can find some example images in the following.
For more details on the training, please follow this link.
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Base model
runwayml/stable-diffusion-v1-5