Instructions to use KamCastle/Grounded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KamCastle/Grounded with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KamCastle/Grounded", 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:
- 52b0ecae24513942426168134b2705f4bfe774630bd1ab9e4c3957f0dbc27d49
- Size of remote file:
- 492 MB
- SHA256:
- 9be66ccfa64e2ac14e9a87dafcc275bd655bc5e3837219ce7c973153dd8fc97c
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