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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bb693b0d04080ad80916fabef0975f3aa596f7d4b02dfb14945fe3e9915f0f98
- Size of remote file:
- 3.44 GB
- SHA256:
- dcc4f9f4a749dc838c712b42c5a2e748354ecddb363fb09d7b824bca2b63df89
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