Text-to-Image
Diffusers
StableDiffusionPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/yeahbouyblend with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/yeahbouyblend 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/yeahbouyblend", 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:
- 40fdb70d8775fc7a883be02f54ca42bbf55d1b20b4aaaf18479f40e9512b224a
- Size of remote file:
- 167 MB
- SHA256:
- 198cf58c6cd245350b11c5f7ac94f9db6aba6719199c4c9c07c59dea65efc8f7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.