Instructions to use CompVis/ldm-celebahq-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/ldm-celebahq-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/ldm-celebahq-256", 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
Adding `safetensors` variant of this model
๐ 1
#7 opened over 1 year ago
by
SFconvertbot
FID scores about the pretrained ldm model
#6 opened about 2 years ago
by
Mqleet
Update vqvae/config.json
๐ 1
#5 opened over 2 years ago
by
david20571015
Create app.py
#4 opened over 2 years ago
by
Jesse1981
Decoder Output
#2 opened over 3 years ago
by
StableDiffuser317
Pipeline output: use `images`
#1 opened over 3 years ago
by
pcuenq