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
FID scores about the pretrained ldm model
#6
by Mqleet - opened
Hi @rromb ,thanks for your great work!
I downloaded ldm-celebahq-256 and sampled with 250 steps, but got a fid of 22.715, which is far away from the results in the github repo https://github.com/CompVis/latent-diffusion#:~:text=Comments-,CelebA%2DHQ,0.49,-https%3A//ommer%2Dlab .
Is there any problem?
Best wishes,
Qianli