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:
- 2d9747d00e2c7d0f4fb6c1a11b6fa4edf190dd79059142c040f994cffc74b322
- Size of remote file:
- 1.39 GB
- SHA256:
- ca9c34533e897b9ba400fa9aed2b84f3c83aba0b6913423855a4af5b82dcdedb
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