Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use kabachuha/gigafractal2-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kabachuha/gigafractal2-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kabachuha/gigafractal2-diffusion", 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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- b157e34fda46e92c26d3d09a2cd294df1e68498cc4768a133655d68319cc8ceb
- Size of remote file:
- 1.36 GB
- SHA256:
- 0d5b08b340a693f23a3cb709d59c85922fbdbb33fc80f0cd12ed9b62c0e25a65
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.