Instructions to use DasDani99/customDiff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DasDani99/customDiff with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DasDani99/customDiff", 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:
- 176bd5fa2a8ab149c98eb632e5599f865e31e4e8885e63c8700c0f34a0561aa5
- Size of remote file:
- 335 MB
- SHA256:
- 68be7f84be07319aa1fe76de5e66e16b60a168e1717b6069dc0e7f2f09b551aa
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