Instructions to use dde/js2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dde/js2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dde/js2", 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:
- 3ae03d8922731cdc4f8c49dfc32e99efd32d0d472cbeafd064534ceeb90b1a1c
- Size of remote file:
- 246 MB
- SHA256:
- 74a6d36904f66d6dfeff5412f6dd703fb4d12ee32ad4d7b702d3bb2c2b92e637
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