Text-to-Image
Diffusers
StableDiffusionXLPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/generator2000xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/generator2000xl 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/generator2000xl", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 67520715394932069c3377dfe660e1ad0b4f223f41bd4b0903c9cd6b859528ce
- Size of remote file:
- 5.14 GB
- SHA256:
- c0b257836a1cae0edf2b2c278e896adb1c43f61a4372106b0f04cb9f0da27c57
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.