Text-to-Image
Diffusers
StableDiffusionXLPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/fffghh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/fffghh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/fffghh", 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:
- dfafabbf41cb79dfacb9396a4ecee270edca024e0ba6be094ae2702a5d05cdf7
- Size of remote file:
- 335 MB
- SHA256:
- aad787b77d42110500c5cf44f95775342fe1bccf457a8172b69a7a439bfcdbe7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.