Text-to-Image
Diffusers
StableDiffusionXLPipeline
ultra-realistic
stable-diffusion
distilled-model
knowledge-distillation
Instructions to use ckpt/SSD-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ckpt/SSD-1B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ckpt/SSD-1B", 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:
- b6fcaca618cb5d8ee4882f3e9a2dba66f1bb5f2faed6be5e43ad70371bd1c2a8
- Size of remote file:
- 4.47 GB
- SHA256:
- e0be832c41f7e965fa0b50d5d9d006ac90dc5596111e5ef71b8775dc57d4de03
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