Instructions to use dallinmackay/JWST-Deep-Space-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dallinmackay/JWST-Deep-Space-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dallinmackay/JWST-Deep-Space-diffusion", 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
Adding `safetensors` variant of this model
#7 opened almost 2 years ago
by
SFconvertbot
Add `scale_factor` to vae config.
#5 opened over 3 years ago
by
valhalla
Add `clip_sample=False` to scheduler to make model compatible with DDIM.
#4 opened over 3 years ago
by
patrickvonplaten
Great for producing depth and starry backgrounds
👍 2
#3 opened over 3 years ago
by
williamcstanford
Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default
#2 opened over 3 years ago
by
patrickvonplaten